Construction Project Managment TechniquesPresentation Transcript
What is Project Management?
A project is made up of a group of interrelated work activities constrained by a specific
scope, budget, and schedule to deliver capital assets needed to achieve the strategic
goals of an Agency. All projects must have a beginning and an end.
The management of construction projects requires knowledge of modern management as well as
an understanding of the design and construction process. Construction projects have a specific set
of objectives and constraints such as a required time frame for completion. While the relevant
technology, institutional arrangements or processes will differ, the management of such projects
has much in common with the management of similar types of projects in other specialty or
technology domains such as aerospace, pharmaceutical and energy developments.
Project management is the art of directing and coordinating human and material resources
throughout the life of a project by using modern management techniques to achieve predetermined
objectives of scope, cost, time, quality and participation satisfaction.
By contrast, the general management of business and industrial corporations assumes a broader
outlook with greater continuity of operations. Nevertheless, there are sufficient similarities as well
as differences between the two so that modern management techniques developed for general
management may be adapted for project management.
The basic ingredients for a project management framework may be represented schematically in
Figure 2-1. A working knowledge of general management and familiarity with the special
knowledge domain related to the project are indispensable. Supporting disciplines such as
computer science and decision science may also play an important role. In fact, modern
management practices and various special knowledge domains have absorbed various techniques
or tools which were once identified only with the supporting disciplines. For example, computer-
based information systems and decision support systems are now common-place tools for general
management. Similarly, many operations research techniques such as linear programming and
network analysis are now widely used in many knowledge or application domains. Hence, the
representation in Figure 2-1 reflects only the sources from which the project management
Figure 2-1: Basic Ingredients in Project Management
Poject management in construction encompasses a set of objectives which may be accomplished
by implementing a series of operations subject to resource constraints. There are potential
conflicts between the stated objectives with regard to scope, cost, time and quality, and the
constraints imposed on human material and financial resources. These conflicts should be
resolved at the onset of a project by making the necessary tradeoffs or creating new alternatives.
Subsequently, the functions of project management for construction generally include the
1. Specification of project objectives and plans including delineation of scope, budgeting,
scheduling, setting performance requirements, and selecting project participants.
2. Maximization of efficient resource utilization through procurement of labor, materials and
equipment according to the prescribed schedule and plan.
3. Implementation of various operations through proper coordination and control of planning,
design, estimating, contracting and construction in the entire process.
4. Development of effective communications and mechanisms for resolving conflicts among the
The Project Management Institute focuses on nine distinct areas requiring project manager
knowledge and attention:
1. Project integration management to ensure that the various project elements are effectively
2. Project scope management to ensure that all the work required (and only the required work) is
3. Project time management to provide an effective project schedule.
4. Project cost management to identify needed resources and maintain budget control.
5. Project quality management to ensure functional requirements are met.
6. Project human resource management to development and effectively employ project
7. Project communications management to ensure effective internal and external
8. Project risk management to analyze and mitigate potential risks.
9. Project procurement management to obtain necessary resources from external sources.
Construction planning is a fundamental and challenging activity in the management and execution
of construction projects. It involves the choice of technology, the definition of work tasks, the
estimation of the required resources and durations for individual tasks, and the identification of
any interactions among the different work tasks. A good construction plan is the basis for
developing the budget and the schedule for work. Developing the construction plan is a critical
task in the management of construction, even if the plan is not written or otherwise formally
recorded. In addition to these technical aspects of construction planning, it may also be necessary
to make organizational decisions about the relationships between project participants and even
which organizations to include in a project. For example, the extent to which sub-contractors will
be used on a project is often determined during construction planning.
The Role of Project Managers:-
A project’s execution is planned and controlled by the project manager. The project
manager is assigned by the Agency, i.e., the Agency’s executive management. The
project manager must have adequate authority to exercise the responsibility of forming
and managing a team for support of the project. The project manager must have prior
experience managing similar projects in the past. If an Agency cannot commit such an
individual with adequate time and resources, the Agency is well advised to outsource
project management services for management of the project. The project manager may
be tasked with management of multiple projects that may require assignment of additional
project managers for support. In such cases the project manager is taking on the role of a program
activities without a project manager. It shows the multiple interactions an Agency faces without a
project manager to manage the work
activities involved in delivering a new capital asset.
project management organization is structured with the assignment of a project manager to
manage project work activities.
Major Types of Construction:-
1. Residential Housing Construction
2. Institutional and Commercial Building Construction
3. Specialized Industrial Construction
4. Infrastructure and Heavy Construction
Different methods of project management:-
1. Critical path method (CPM)
2. Program evaluation and review technique (PERT)
3. Lean construction method
4. Just in time method
5. Ant colony optimization
6. Monte Carlo method
7. Line of balance method (LOB)
Description of Methods
1.Critical path method (CPM):-
In 1957, DuPont developed a project management method designed to address the challenge of
shutting down chemical plants for maintenance and then restarting the plants once the
maintenance had been completed. Given the complexity of the process, they developed the
Critical Path Method (CPM) for managing such projects.
CPM provides the following benefits:
• Provides a graphical view of the project.
• Predicts the time required to complete the project.
• Shows which activities are critical to maintaining the schedule and which are not.
CPM models the activities and events of a project as a network. Activities are depicted as nodes
on the network and events that signify the beginning or ending of activities are depicted as arcs or
lines between the nodes. The following is an example of a CPM network diagram:
Steps in CPM Project Planning
1. Specify the individual activities.
2. Determine the sequence of those activities.
3. Draw a network diagram.
4. Estimate the completion time for each activity.
5. Identify the critical path (longest path through the network)
6. Update the CPM diagram as the project progresses.
1. Specify the Individual Activities
From the work breakdown structure, a listing can be made of all the activities in the project. This
listing can be used as the basis for adding sequence and duration information in later steps.
2. Determine the Sequence of the Activities
Some activities are dependent on the completion of others. A listing of the immediate
predecessors of each activity is useful for constructing the CPM network diagram.
3. Draw the Network Diagram
Once the activities and their sequencing have been defined, the CPM diagram can be drawn. CPM
originally was developed as an activity on node (AON) network, but some project planners prefer
to specify the activities on the arcs.
4. Estimate Activity Completion Time
The time required to complete each activity can be estimated using past experience or the
estimates of knowledgeable persons. CPM is a deterministic model that does not take into account
variation in the completion time, so only one number is used for an activity's time estimate.
5. Identify the Critical Path
The critical path is the longest-duration path through the network. The significance of the critical
path is that the activities that lie on it cannot be delayed without delaying the project. Because of
its impact on the entire project, critical path analysis is an important aspect of project planning.
The critical path can be identified by determining the following four parameters for each activity:
• ES - earliest start time: the earliest time at which the activity can start given that its precedent
activities must be completed first.
• EF - earliest finish time, equal to the earliest start time for the activity plus the time required
to complete the activity.
• LF - latest finish time: the latest time at which the activity can be completed without delaying
• LS - latest start time, equal to the latest finish time minus the time required to complete the
The slack time for an activity is the time between its earliest and latest start time, or between its
earliest and latest finish time. Slack is the amount of time that an activity can be delayed past its
earliest start or earliest finish without delaying the project.
The critical path is the path through the project network in which none of the activities have slack,
that is, the path for which ES=LS and EF=LF for all activities in the path. A delay in the critical
path delays the project. Similarly, to accelerate the project it is necessary to reduce the total time
required for the activities in the critical path.
6. Update CPM Diagram
As the project progresses, the actual task completion times will be known and the network
diagram can be updated to include this information. A new critical path may emerge, and
structural changes may be made in the network if project requirements change.
CPM was developed for complex but fairly routine projects with minimal uncertainty in the
project completion times. For less routine projects there is more uncertainty in the completion
times, and this uncertainty limits the usefulness of the deterministic CPM model. An alternative to
CPM is the PERT project planning model, which allows a range of durations to be specified for
2.Program evaluation and review technique (PERT):-
Complex projects require a series of activities, some of which must be performed sequentially and
others that can be performed in parallel with other activities. This collection of series and parallel
tasks can be modeled as a network.
In 1957 the Critical Path Method (CPM) was developed as a network model for project
management. CPM is a deterministic method that uses a fixed time estimate for each activity.
While CPM is easy to understand and use, it does not consider the time variations that can have a
great impact on the completion time of a complex project.
The Program Evaluation and Review Technique (PERT) is a network model that allows for
randomness in activity completion times. PERT was developed in the late 1950's for the U.S.
Navy's Polaris project having thousands of contractors. It has the potential to reduce both the time
and cost required to complete a project.
The Network Diagram
In a project, an activity is a task that must be performed and an event is a milestone marking the
completion of one or more activities. Before an activity can begin, all of its predecessor activities
must be completed. Project network models represent activities and milestones by arcs and nodes.
PERT originally was an activity on arc network, in which the activities are represented on the
lines and milestones on the nodes. Over time, some people began to use PERT as an activity on
node network. For this discussion, we will use the original form of activity on arc.
The PERT chart may have multiple pages with many sub-tasks. The following is a very simple
example of a PERT diagram:
The milestones generally are numbered so that the ending node of an activity has a higher number
than the beginning node. Incrementing the numbers by 10 allows for new ones to be inserted
without modifying the numbering of the entire diagram. The activities in the above diagram are
labeled with letters along with the expected time required to complete the activity.
Steps in the PERT Planning Process
PERT planning involves the following steps:
1. Identify the specific activities and milestones.
2. Determine the proper sequence of the activities.
3. Construct a network diagram.
4. Estimate the time required for each activity.
5. Determine the critical path.
6. Update the PERT chart as the project progresses.
1. Identify Activities and Milestones
The activities are the tasks required to complete the project. The milestones are the events
marking the beginning and end of one or more activities. It is helpful to list the tasks in a table that
in later steps can be expanded to include information on sequence and duration.
2. Determine Activity Sequence
This step may be combined with the activity identification step since the activity sequence is
evident for some tasks. Other tasks may require more analysis to determine the exact order in
which they must be performed.
3. Construct the Network Diagram
Using the activity sequence information, a network diagram can be drawn showing the sequence
of the serial and parallel activities. For the original activity-on-arc model, the activities are
depicted by arrowed lines and milestones are depicted by circles or "bubbles".
If done manually, several drafts may be required to correctly portray the relationships among
activities. Software packages simplify this step by automatically converting tabular activity
information into a network diagram.
4. Estimate Activity Times
Weeks are a commonly used unit of time for activity completion, but any consistent unit of time
can be used.
A distinguishing feature of PERT is its ability to deal with uncertainty in activity completion
times. For each activity, the model usually includes three time estimates:
• Optimistic time - generally the shortest time in which the activity can be completed. It is
common practice to specify optimistic times to be three standard deviations from the mean so
that there is approximately a 1% chance that the activity will be completed within the
• Most likely time - the completion time having the highest probability. Note that this time is
different from the expected time.
• Pessimistic time - the longest time that an activity might require. Three standard deviations
from the mean is commonly used for the pessimistic time.
PERT assumes a beta probability distribution for the time estimates. For a beta distribution, the
expected time for each activity can be approximated using the following weighted average:
Expected time = ( Optimistic + 4 x Most likely + Pessimistic ) / 6
This expected time may be displayed on the network diagram.
To calculate the variance for each activity completion time, if three standard deviation times were
selected for the optimistic and pessimistic times, then there are six standard deviations between
them, so the variance is given by:
[ ( Pessimistic - Optimistic ) / 6 ]2
5. Determine the Critical Path
The critical path is determined by adding the times for the activities in each sequence and
determining the longest path in the project. The critical path determines the total calendar time
required for the project. If activities outside the critical path speed up or slow down (within
limits), the total project time does not change. The amount of time that a non-critical path activity
can be delayed without delaying the project is referred to as slack time.
If the critical path is not immediately obvious, it may be helpful to determine the following four
quantities for each activity:
• ES - Earliest Start time
• EF - Earliest Finish time
• LS - Latest Start time
• LF - Latest Finish time
These times are calculated using the expected time for the relevant activities. The earliest start and
finish times of each activity are determined by working forward through the network and
determining the earliest time at which an activity can start and finish considering its predecessor
activities. The latest start and finish times are the latest times that an activity can start and finish
without delaying the project. LS and LF are found by working backward through the network. The
difference in the latest and earliest finish of each activity is that activity's slack. The critical path
then is the path through the network in which none of the activities have slack.
The variance in the project completion time can be calculated by summing the variances in the
completion times of the activities in the critical path. Given this variance, one can calculate the
probability that the project will be completed by a certain date assuming a normal probability
distribution for the critical path. The normal distribution assumption holds if the number of
activities in the path is large enough for the central limit theorem to be applied.
Make adjustments in the PERT chart as the project progresses. As the project unfolds, the
estimated times can be replaced with actual times. In cases where there are delays, additional
resources may be needed to stay on schedule and the PERT chart may be modified to reflect the
Benefits of PERT
PERT is useful because it provides the following information:
• Expected project completion time.
• Probability of completion before a specified date.
• The critical path activities that directly impact the completion time.
• The activities that have slack time and that can lend resources to critical path activities.
• Activity start and end dates.
The following are some of PERT's weaknesses:
• The activity time estimates are somewhat subjective and depend on judgement. In cases where
there is little experience in performing an activity, the numbers may be only a guess. In other
cases, if the person or group performing the activity estimates the time there may be bias in
• Even if the activity times are well-estimated, PERT assumes a beta distribution for these time
estimates, but the actual distribution may be different.
• Even if the beta distribution assumption holds, PERT assumes that the probability distribution
of the project completion time is the same as the that of the critical path. Because other paths
can become the critical path if their associated activities are delayed, PERT consistently
underestimates the expected project completion time.
The underestimation of the project completion time due to alternate paths becoming critical is
perhaps the most serious of these issues. To overcome this limitation, Monte Carlo simulations
can be performed on the network to eliminate this optimistic bias in the expected project
3. Lean construction method
Managing construction under Lean is different from typical contemporary practice
has a clear set of objectives for the delivery process,
is aimed at maximizing performance for the customer at the project level,
designs concurrently product and process, and
applies production control throughout the life of the project.
By contrast, the current form of production management in construction is derived from the
same activity centered approach found in mass production and project management. It aims
to optimize the project activity by activity, assuming customer value has been identified in
design. Production is managed throughout a project by first breaking the project into pieces,
i.e. design and construction, then putting those pieces in a logical sequence, estimating the
time and resources required to complete each activity and therefore the project. Each piece or
activity is further decomposed until it is contracted out or assigned to a task leader, foreman
or squad boss. Control is conceived as monitoring each contract or activity against its
schedule and budget projections. These projections are rolled up to project level reports. If
Reliable workflow was a consequence of stopping the line rather than a stated objective.
activities or chains along the critical path fall behind, efforts are made to reduce cost and
duration of the offending activity or changing the sequence of work. If these steps do not
solve the problem, it is often necessary to trade cost for schedule by working out of the best
sequence to make progress. The focus on activities conceals the waste generated between
continuing activities by the unpredictable release of work and the arrival of needed resources.
Simply put, current forms of production and project management focus on activities and
ignore flow and value considerations (Koskela 1992, Koskela and Huovila 1997).
Managing the combined effect of dependence and variation is a first concern in lean
production. Goldratt (1986) illustrates the effects on production in “The Goal” and the
application to construction is demonstrated by Tommelein et al. (1999) in “Parade of Trades.
The problem of dependence and variation can be illustrated by what happens in heavy traffic
on a freeway. If every car drove at exactly the same speed then spacing between cars could
be very small and the capacity of the freeway would be limited by whatever speed was set.
Each car would be dependent on the one ahead to release pavement and variation would be
zero. In effect, there would be no inventory of unused pavement. In reality of course, each
car does use the pavement released to it from the car ahead but speeds vary.
Under the pressure to get to work or home, gaps between cars close and any variation in
speed demands immediate response from following cars. As the gaps close, small variations
in speed propagate along and across lanes. One small hesitation can lead to a huge standing
wave as traffic slows to a crawl. Recovery is difficult because it is impossible to get everyone
to accelerate smoothly back up to the standard speed and interval. High speed at any one
moment does not assure minimum travel time in conditions of dependence and variation. The
idea that you do not get home any faster by driving as fast and as close to the car ahead is
counter intuitive (at least to teenagers). Certainly the system itself does not function as well
when dependence is tighter and variation greater.
Managing the interaction between activities, the combined effects of dependence and
variation, is essential if we are to deliver projects in the shortest time. Minimizing the
combined effects of dependence and variation becomes a central issue for the planning and
control system as project duration is reduced and the complexity increases. (Complexity is
defined by the number of pieces or activities that can interact.) The need to improve
reliability in complex and quick circumstances is obvious. New forms of planning and
control are required.
The first goal of lean construction must be to fully understand the underlying “physics”
of production, the effects of dependence and variation along supply and assembly chains.
These physical issues are ignored in current practice which tend to focus on teamwork,
communication and commercial contracts. These more human issues are at the top of
practitioner’s lists of concerns because they do not, indeed cannot see the source of their
problems. It is not that these people are stupid, but that they lack the language and conceptual
foundation to understand the problem in physical production terms. The development of
partnering illustrates this point.
Partnering makes great sense from an activity perspective. But few realize Partnering is a
solution to the failure of central control to manage production in conditions of high
uncertainty and complexity. In these circumstances, representatives of each activity (or
contract) must be able to communicate directly with out relying on the central authority tol
control message flow, and so Partnering works. From the lean understanding of the physics
of production, Partnering is evidence of a failure in production management but it provides
the opportunity for collaborative redesign of the planning system to support close
coordination and reliable work flow.
Lean supports the development of team work and a willingness to shift burdens along
supply chains. Partnering relationships coupled with lean thinking make rapid
implementation possible. Where Partnering is about building trust, lean is about building
reliability. Trust is the human attitude that arises in conditions of reliability. We are not likely
to trust one another very long if we do not demonstrate reliability. Reliability is the result of
the way systems are designed. Of course people manage systems and in current terms they do
a fine job. The problem is that production systems just do not work well when every person
tries to optimize their performance without understanding how their actions affect the larger
The problem of matching labor to available work offers a good example of the difference
between the contemporary view of the workplace and lean. “Matching labor to work” means
having the resources on hand for a crew to work steadily and without interruption. Current
practice views the assignment to the crew as a sort of “mini contract” which is more or less
independent of other assignments, and sets the person in charge responsible for the
organization of resources and direction of the crew. To be fair, companies have logistics
systems that try to get the resources close to the crew and a few actually try to assemble and
assign packages of work. But the majority of foremen are responsible for the final collection
of resources and assuring that their crews can work continuously. When this approach fails to
produce acceptable results, when the numbers are bad, management assumes the foreman or
crew is not performing.
Companies typically maintain elaborate cost control systems to measure this
performance. These systems are the manifestations of the cause and effect theories operating
in the company. At the heart of this model is the belief that the crew is essentially
independent and that all costs charged to an account arise within from the effort necessary to
complete the assignment by the crew.
The lean construction view is different as it views the problem in physical production
terms. The crew works at variable rates using resources supplied at varying rates. Matching
labor to available work is a difficult systems design problem with a limited number of
“solutions.” Lean works to isolate the crew from variation in supply by providing an
adequate backlog (a safe distance between cars) or tries to maintain excess capacity in the
crew so they can speed up or slow as conditions dictate. On occasion, people acting on
intuition apply these techniques. (They drive to work on freeways.) Unfortunately neither
resource nor capacity buffers reduce the variation in supply and use rates of downstream
These problems are solved by long and predictable runs in the factories (and along the
highways of our dreams). In these stable circumstances managers can predict the work
content at each station and shift labor along the line to minimize imbalance. Such factories
are mostly dreams that have little to do with construction where we only have some idea of
the labor content of activities from previous projects.
People holding current practice dear sometimes say they are helpless victims of fate when
faced with managing uncertainty on projects. Their view is that uncertainty arises in other
activities beyond their control. The lean approach is to assure we do not contribute to
variation in work flow and to decouple when we cannot get it under control. In lean
construction as in much of manufacturing, planning and control are two sides of a coin that
keeps revolving throughout a project.
Planning: defining criteria for success and producing strategies for achieving
Control: causing events to conform to plan and triggering learning and replanning.
Often the first question we are asked when describing a project to people unfamiliar with
lean thinking is, “What kind of contract was in force?” Next come organizational and
systems issues: “Was supervision by area or craft? Union or not? Were designers on site?
Did the owner know what they wanted?” These questions are reflections of contracting or
activity centered thinking. Lean construction rests on a production management mind. We
ask about the way work itself is planned and managed. We want to know the whether the
planning system itself is under control, the location of inventories and excess capacity, and
the extent to which the design and construction process itself supports customer value.
Lean construction embraces uncertainty in supply and use rates as the first great
opportunity and employ production planning to make the release of work to the next crew
more predictable, and then we work within the crews to understand the causes of variation.
4. Just in time method
The acronym JIT has been highly visible since the late 1980's, as
manufacturing attempted to meet competitive challenges by adopting
newly emerging management theories and techniques. What is JIT?
Manufacturing JIT is a method of pulling work forward from one
process to the next "just-in-time"; i.e. when the successor process needs it,
ultimately producing throughput. One benefit of manufacturing JIT is
reducing work-in-process inventory, and thus working capital. An even
greater benefit is reducing production cycle times, since materials spend
less time sitting in queues waiting to be processed. However, the greatest
benefit of manufacturing JIT is forcing reduction in flow variation, thus
contributing to continuous, ongoing improvement. Can this approach be
applied to construction? What is "Construction JIT"?
Construction JIT vs Manufacturing JIT
JIT is a technique developed by Taichi Ohno and his fellow workers
at Toyota . Ohno's fundamental purpose was to change production's
directives from estimates of demand to actual demand--a purpose
originally rooted in the absence of a mass market and the need to
produce small lots of many product varieties.
In assembly line production systems managed by lean production
concepts, the directives for production are provided by means of kanban
from downstream processes. This system insures that whatever is
produced is throughput, i.e. is needed for the production of an order.
Kanban works as a near-term adjusting mechanism within a system of
production scheduling that strives for firm and stable aggregate output
quantities, and provides all suppliers in the extended process
progressively more specific production targets as the plan period
approaches, resulting ultimately in a firm 2-6 week production schedule.
This system provides sufficient flexibility to adjust to actual demand,
while assuring that all resources are applied to the production of
In manufacturing, the need for flexibility comes from a potential
difference between forecast and actual demand. Many products are being
produced, so it is important to minimize the time required to produce any
specific type of product demanded. In construction, there is only one
product produced once. And in the case of industrial construction, that
product is the facility for producing manufacturing's products. It is
consequently important to reduce the time needed to produce the facility,
not necessarily the time to produce any component. (NB: This fact often
conflicts with the different interests of the various organizations involved
in a project.) Further, changes arise from progressive definition of
customer wants, so flexibility is needed in order to respond to latebreaking
The application of JIT to construction differs substantially from its
application to manufacturing because construction and manufacturing
are different types of production, and because of the greater complexity
and uncertainty of construction.
The extent and significance of uncertainty in construction has been
adequately addressed in earlier papers but a moment's reflection
supports the view that construction is complex. The number of parts,
relative lack of standardization, and the multiple participants and
constraining factors easily make the construction of an automobile
factory more difficult than the production of an automobile in that
factory. When this complexity is joined with economic pressures to
minimize time and cost, that uncertainty results is not surprising. But is
construction really a different type of production than manufacturing, or
simply a more complex and uncertain version of manufacturing itself?
What kind of production is construction?
Construction is the final component in manufacturing's product
development process. Construction is complete before manufacturing's
production begins. Consequently, it is misleading to conceive construction
as analogous to factory production (although some aspects of
construction fit better in that analogy; i.e. fabrication). Construction is
best conceived as a product development process, extending from product
design through process design to facility (the manufacturing process tool)
construction, the end result of which is readiness for manufacturing.
Admittedly, this is a best fit in the case of industrial construction,
and becomes less plausible as we move toward the cookie cutter end of
the industry spectrum, e.g. manufactured housing. There seems to be a
gray zone between manufacturing and construction, where the work looks
like construction because final assembly is done where the facility is to be
used, but looks like manufacturing because all that remains of the process
is to match production output with sales. This gray zone is obviously ripe
for industrialization and mechanization, which ultimately pushes it over
into the camp of manufacturing. The proper business of construction is
completing product and process design. Once that is done, it is but a
matter of time before wit and invention capture mere assembly for
Uncertainty is a necessary component in construction conceived as a
product development process. The very purpose of the process is to
surface and resolve trade-offs between means and ends, all the way from
product design through facility construction. The management of projects
so conceived is the proper terrain for lean construction concepts and
techniques. So, construction is a different type of production than
manufacturing, and has greater uncertainty and flow variation. Is there
an application for JIT in construction?
Using JIT to reduce variation and waste: Manufacturing vs
By minimizing inventories between processes, Ohno removed the
safety stock that allowed a downstream process to continue working when
a feeder process failed. He also required that operators stop the
production line when they were unable to fix problems.
5. Ant colony optimization
The ant colony optimization algorithm (ACO), is a probabilistic technique for solving
computational problems which can be reduced to finding good paths through graphs.
This algorithm is a member of ant colony algorithms family, in swarm intelligence methods, and
it constitutes some met heuristic optimizations. Initially proposed by Marco Dorigo in 1992 in his
PhD thesis   , the first algorithm was aiming to search for an optimal path in a graph; based on
the behavior of ants seeking a path between their colony and a source of food. The original idea
has since diversified to solve a wider class of Numerical problems, and as a result, several
problems have emerged, drawing on various aspects of the behavior of ants
In the real world, ants (initially) wander randomly, and upon finding food return to their colony
while laying down pheromone trails. If other ants find such a path, they are likely not to keep
travelling at random, but to instead follow the trail, returning and reinforcing it if they eventually
find food (see Ant communication).
Over time, however, the pheromone trail starts to evaporate, thus reducing its attractive strength.
The more time it takes for an ant to travel down the path and back again, the more time the
pheromones have to evaporate. A short path, by comparison, gets marched over faster, and thus
the pheromone density remains high as it is laid on the path as fast as it can evaporate. Pheromone
evaporation has also the advantage of avoiding the convergence to a locally optimal solution. If
there were no evaporation at all, the paths chosen by the first ants would tend to be excessively
attractive to the following ones. In that case, the exploration of the solution space would be
Thus, when one ant finds a good (i.e., short) path from the colony to a food source, other ants are
more likely to follow that path, and positive feedback eventually leads all the ants following a
single path. The idea of the ant colony algorithm is to mimic this behavior with "simulated ants"
walking around the graph representing the problem to solve.
The original idea comes from observing the exploitation of food resources among ants, in which
ants’ individually limited cognitive abilities have collectively been able to find the shortest path
between a food source and the nest.
1. The first ant finds the food source (F), via any way (a), then returns to the nest (N), leaving
behind a trail pheromone (b)
2. Ants indiscriminately follow four possible ways, but the strengthening of the runway makes it
more attractive as the shortest route.
3. Ants take the shortest route, long portions of other ways lose their trail pheromones.
In a series of experiments on a colony of ants with a choice between two unequal length paths
leading to a source of food, biologists have observed that ants tended to use the shortest route. 
A model explaining this behaviour is as follows:
1. An ant (called "blitz") runs more or less at random around the colony;
2. If it discovers a food source, it returns more or less directly to the nest, leaving in its path a
trail of pheromone;
3. These pheromones are attractive, nearby ants will be inclined to follow, more or less directly,
4. Returning to the colony, these ants will strengthen the route;
5. If two routes are possible to reach the same food source, the shorter one will be, in the same
time, traveled by more ants than the long route will
6. The short route will be increasingly enhanced, and therefore become more attractive;
7. The long route will eventually disappear, pheromones are volatile;
8. Eventually, all the ants have determined and therefore "chosen" the shortest route.
Ants use the environment as a medium of communication. They exchange information indirectly
by depositing pheromones, all detailing the status of their "work". The information exchanged has
a local scope, only an ant located where the pheromones were left has a notion of them. This
system is called "Stemberg" and occurs in many social animal societies (it has been studied in the
case of the construction of pillars in the nests of termites). The mechanism to solve a problem too
complex to be addressed by single ants is a good example of a self-organized system. This system
is based on positive feedback (the deposit of pheromone attracts other ants that will strengthen it
themselves) and negative (dissipation of the route by evaporation prevents the system from
thrashing). Theoretically, if the quantity of pheromone remained the same over time on all edges,
no route would be chosen. However, because of feedback, a slight variation on an edge will be
amplified and thus allow the choice of an edge. The algorithm will move from an unstable state in
which no edge is stronger than another, to a stable state where the route is composed of the
Ant colony optimization algorithms have been applied to many combinatorial optimization
problems, ranging from quadratic assignment to fold protein or routing vehicles and a lot of
derived methods have been adapted to dynamic problems in real variables, stochastic problems,
multi-targets and parallel implementations. It has also been used to produce near-optimal solutions
to the travelling salesman problem. They have an advantage over simulated annealing and genetic
algorithm approaches of similar problems when the graph may change dynamically; the ant
colony algorithm can be run continuously and adapt to changes in real time. This is of interest in
network routing and urban transportation systems.
As a very good example, ant colony optimization algorithms have been used to produce near-
optimal solutions to the travelling salesman problem. The first ACO algorithm was called the Ant
system  and it was aimed to solve the travelling salesman problem, in which the goal is to find
the shortest round-trip to link a series of cities. The general algorithm is relatively simple and
based on a set of ants, each making one of the possible round-trips along the cities. At each stage,
the ant chooses to move from one city to another according to some rules:
1. It must visit each city exactly once;
2. A distant city has less chance of being chosen (the visibility);
3. The more intense the pheromone trail laid out on an edge between two cities, the greater the
probability that that edge will be chosen;
4. Having completed its journey, the ant deposits more pheromones on all edges it traversed, if
the journey is short;
5. After each iteration, trails of pheromones evaporate
6. Monte Carlo method
What is Monte Carlo Simulation?
Monte Carlo simulation, or probability simulation, is a technique used to understand the impact of
riskand uncertainty in financial, project management, cost, and other forecasting models.
How It Works
In a Monte Carlo simulation, a random value is selected for each of the tasks, based on the range
of estimates. The model is calculated based on this random value. The result of the model is
recorded, and the process is repeated. A typical Monte Carlo simulation calculates the model
hundreds or thousands of times, each time using different randomly-selected values.
When the simulation is complete, we have a large number of results from the model, each based
random input values. These results are used to describe the likelihood, or probability, of reaching
various results in the model.
For example, consider the model described above: we are estimating the total time it will take to
complete a particular project. In this case, it's a construction project, with three parts. The parts
to be done one after the other, so the total time for the project will be the sum of the three parts.
All the times are in months.
Task Time Estimate
Job 1 5 Months
Job 2 4 Months
Job 3 5 Months
Total 14 Months
Table 1: Basic Forecasting Model
In the simplest case, we create a single estimate for each of the three parts of the project. This
model gives us a result for the total time: 14 months. But this value is based on three estimates,
each of which is an unknown value. It might be a good estimate, but this model can't tell us
anything about risk.
How likely is it that the project will be completed on time?
To create a model we can use in a Monte Carlo simulation, we create three estimates for each part
of the project. For each task, we estimate the minimum and maximum expected time (based on
experience, or expertise, or historical information). We use these with the “most likely” estimate,
one that we used above:
Task Minimum Most Likely Maximum
Job 1 4 Months 5 Months 7 Months
Job 2 3 Months 4 Months 6 Months
Job 3 4 Months 5 Months 6 Months
Total 11 Months 14 Months 19 Months
Table 2: Forecasting Model Using Range Estimates
What is Monte Carlo Simulation?
This model contains a bit more information. Now there is a range of possible outcomes. The
might be completed in as little as 11 months, or as long as 19 months.
In the Monte Carlo simulation, we will randomly generate values for each of the tasks, then
calculate the total time to completion1. The simulation will be run 500 times. Based on the results
of the simulation, we will be able to describe some of the characteristics of the risk in the model.
To test the likelihood of a particular result, we count how many times the model returned that
result in the simulation. In this case, we want to know how many times the result was less than or
equal to a particular number of months.
Time Number of Times (Out of 500) Percent of Total (Rounded)
12 Months 1 0%
13 Months 31 6%
14 Months 171 34%
15 Months 394 79%
16 Months 482 96%
17 Months 499 100%
18 Months 500 100%
Table 3: Results of a Monte Carlo Simulation
The original estimate for the “most likely”, or expected case, was 14 months. From the Monte
simulation, however, we can see that out of 500 trials using random values, the total time was 14
months or less in only 34% of the cases.
Put another way, in the simulation there is only a 34% chance – about 1 out of 3 – that any
individual trial will result in a total time of 14 months or less. On the other hand, there is a 79%
chance that the project will be completed within 15 months. Further, the model demonstrates that
it is extremely unlikely, in the simulation, that we will ever fall at the absolute minimum or
maximum total values.
This demonstrates the risk in the model. Based on this information, we might make different
when planning the project. In construction, for example, this information might have an impact on
our financing, insurance, permits, and hiring needs. Having more information about risk at the
beginning means we can make a better plan for going forward.
7. Detailed description of Line of balance method (LOB):-
The Line of Balance (otherwise known as ‘Time-Distance’ or ‘Time-Chainage’) diagram is a
graphical technique particularly suited for projects that comprise multiple and similar units, such
as residential housing. The x-axis represents time and the y-axis the number of units (or similarly
may represent the extent of the work site). Sloping lines represent the activities of the project,
the gradient of the line indicating the rate of production.i
A Line of Balance (LOB) chart does not show direct relationships between individual activities; it
shows an output relationship between different operations in that one operation must be
completed at a particular rate for the subsequent relationship to proceed at the required rate.
Maintaining the theme of house building, the following graphic illustrates a LOB chart for a few
simple house construction activities:
Simple Line of Balance diagram illustrating house constructionii
The Gantt chart is a popular type of bar chart that illustrates a project schedule. Gantt charts
illustrate the start and finish dates of the activities and summary elements of a project. Activities
and summary elements comprise the work breakdown structure of the project. Some Gantt
charts also show the dependency (i.e. precedence network) relationships between activities.iii
A simple example of a Gantt chart based on the same example as used for the Line of Balance
definition is shown below:
Gantt chart showing simple house construction projectiv
The Development of the Two Separate Methods
The Line of Balance (LOB) technique was originated by the Goodyear Company in the early
1940's and was developed by the U.S. Navy in the early 1950's for the programming and control
of both repetitive and non-repetitive projects. LOB was first applied to industrial manufacturing
and production control, where the objective was to attain or evaluate a production line flow rate
of finished products.
The basic concepts of LOB have since been applied in the construction industry as a planning
and scheduling method. Several attempts either to modify the basic LOB technique or to
develop variations named differently have also been made (Examples, to name a few include:
velocity diagrams, the construction planning technique, the vertical production method, the
linear scheduling method, time space scheduling method, and repetitive project model)v.
Henry Laurence Gantt (1861-1919) was a mechanical engineer, industry advisor and
management consultant. He developed first examples of Gantt charts in 1910. Gantt charts were
used as a visual tool to illustrate the start and finish dates of the terminal elements and summary
elements of a project. Accepted as a commonplace project management tool today, it was an
innovation of world-wide importance at that time. Gantt charts were used in large construction
projects like the Hoover Dam started in 1931, and the USA interstate highway system started in
In the 1980s, personal computers eased the creation and editing of elaborate Gantt charts, and
they have since been developed from simple linked bar charts into network (or precedence)
diagrams and are widely used for planning and scheduling projects.
The Current Application of these Methods:-
Today, the Gantt chart is accepted as a commonplace project management tool. This method,
via the numerous desktop computer applications that are available, is primarily used by project
managers and project planners in the management of projects.
It is popular because it allows you to estimate how long a project should take, lays out the order
in which tasks need to be carried out, helps manage dependencies between tasks, determines the
resources needed, monitors progress and helps to see how remedial action may bring the project
back on course. You can also immediately see what should be done at some point in time. All
this is done through the assistance of the software packages whose analysis is based on network
analysis and illustrated by way of the Gantt chart.
LOB has not been fully developed and implemented by the construction industry because of the
immense popularity of network techniques including Critical Path Methods. Even though the
development of LOB predates the other techniques, the development of these other techniques
has overtaken it and it would seem that LOB is only used for specific types of projects such as
the resource scheduling and coordination of subcontractors, highway pavement construction
projects, modelling production activities for multi-facility projects, pipeline and transportation
A typical project is a housing project consisting of several houses where the same type of work
such as foundations, brickwork, roof construction, and internal trades are undertaken on each
The Benefits of the Line of Balance Method:-
Network analysis methods are very popular in larger projects but present complications in
projects of repetitive nature such as high-rise building construction. Critical Path Method (CPM)
based techniques have been criticized for their inability to model repetitive projects. The first
problem is the sheer size of the network. In repetitive projects of n units, the network prepared
for one unit has to be repeated n times and linked to each other; this results in a huge network
that is difficult to manage. This may cause difficulties in communication among the members of
the construction management team and difficulties in foreseeing the likely effect of delays. The
second problem is that the Critical Path Method of analysis used in network analysis is designed
primarily for optimizing project duration rather than adequately dealing with the special resource
constraints of repetitive projects. Indeed, the critical path method has no capability to assure a
smooth procession of labour teams from unit to unit with no conflict and no idle time for
workers and equipment. This leads to hiring and procurement problems in the flow of labour
and material during construction.vii
The Line of Balance (LOB) method of scheduling is well suited to projects that are composed of
activities of a linear and repetitive nature. The major benefits of this method are that it provides
production rate and duration information in the form of an easily interpreted graphics format
and that it allows a smooth and efficient flow of resources.
Thus, it is clear that the LOB method allows a better grasp of a project composed of repetitive
activities than any other scheduling technique, because it allows the possibility to adjust the rate
of production of activities. The diagram can be progressed by plotting on the chart the work
achieved. This will then show at a glance what is wrong with the progress of an activity, and can
detect potential future bottlenecks. If the rate at which the work is being achieved is lower than
required, adjustments can be made to increase the output.
An example of this is illustrated below, using the house construction chart illustrated earlier. The
chart has now been updated to week 12 of the project. It can be seen that the ‘Foundations’ output
has fluctuated but that they are generally on schedule and almost complete. The ‘Brickwork’ and
‘Roof Construction’ are both though running behind schedule and the ‘Internal Works’ have not
started. By extrapolation though it can be seen that the first unit will be completed over 3 weeks
late. The overall project delay could also be determined by extrapolation, and using the same
house building example it can be determined that it would result in an overall delay of over 10
Progressed Line of Balance diagram illustrating how the effect of lower
productivity has the potential to delay the house constructionviii
The above LOB method diagram illustrates clearly the activities that are running late. This
diagram can then be used as a project management tool to assess ways to mitigate the delay. The
mitigation would generally be in the form of increasing the output of the activity (either in the
form of increasing the efficiency or by increasing the resource employed on the activity) and
would be observed on the LOB diagram as an increase in the gradient of the activity line.
Using the house building project above as an example, by increasing the output for the
‘Brickwork’ and ‘Roof Construction’ the current observed output deficit can be minimised with
effect of reducing the overall delay. The amount of delay reduction relies on the improvement of
the activity output.
The essence of the LOB document is therefore one of output and productivity. In this respect
the document can have use in the process of claims for delay and/or disruption. If the LOB
document is produced contemporaneously it can identify any areas of low output or delay by
other causes thus enabling the circumstances to be addressed at the time. The chart thus
becomes a good illustration of any genuine claim for delay and/or disruption.
Finally, the LOB method requires less time and effort to produce than network schedules, and
can be generated on software as simple as Microsoft word and excel or can be prepared slickly
and efficiently using proprietary software.
The Down Side of Line of Balance:-
Line of Balance diagrams are not well suited to individual activities that have a short duration
and that are undertaken in isolation to similar activities in a project.
The method, and hence the diagram, also becomes more difficult and complex when dealing
with large construction projects consisting of a large number of inter-related activities. In these
situations the diagram may only be effective if illustrating summaries of groups of activities and
hence can only be effective as an over-view document; whereas a Gantt chart allows an
assessment as to how long a project should take, lays out the order in which tasks need to be
carried out and helps manage the dependencies between tasks.ix
A LOB diagram on the other hand does not show exact relationships between individual
activities in the same way as a Gantt chart does, and hence it is not easy to demonstrate a critical
path through the works. For more complex projects this would become impossible except at a
summarised over-view level.
For this reason Gantt charts tend to be the favoured option by Clients, and it is unlikely at
present for a LOB diagram to be accepted by Clients as either a Tender or a Contract
CAN LINE OF BALANCE PROGRAMMES SUPERSEDE GANTT CHARTS INTHE
Both the Gantt chart and the Line of Balance diagram are techniques used in the construction
industry to illustrate the planned sequence of work and to allow adjustments due to changed
circumstances. The Gantt chart is the most widely used of the techniques; perceived by the
Construction Industry as being the easiest and most recognisable form of programming. The
Line of Balance method is less known and tends to be used on projects where there is a high
degree of repetitive work.
This article explains the different methods, what they look like and reviews the pros and cons of
each. It also investigates whether the Line of Balance method could ever supersede the Gantt
There are potentially very few projects where a LOB diagram cannot be used and be of benefit.
As seen above though, for more complex projects this perhaps may only be at a summarised
level. Generally, for all main works and main subcontractors, it will assist in the management of
both the subcontractor and the project.
The diagrams are usually much easier to read than a detailed Gantt chart, making it a good tool
for reporting purposes and for illustrating the inter-relationship between different activities.
The LOB method is not simple though when dealing with a construction project that is broken
down into a large number of activities that are bound by numerous and complicated
relationships and other constraints. The ensuing diagram is not as effective and can prove more
complicated to read than the traditional Gantt chart.
Contractually, network analysis diagrams illustrating the project critical path(s) such as the Gantt
chart appear to be the requisite of clients, and are favoured in dispute resolutions.
Thus it appears that it is unlikely that the Line of Balance method shall, in the near future, take
over as being the main method used in the construction industry.
It has been seen though that there is much that the method can offer as a project management
tool, and may fruitfully be used in conjunction with a network analysis method such as the Gantt