Supply Chain in logistics and planning

1. IOBM
LOGISTICS PLANNING

2. The Increased Importance of Logistics
• A Reduction in Economic Regulation
• Recognition by Prominent Non-Logisticians
• Technological Advances
• The Growing Power of Retailers
• Globalization of Trade
Three objectives of logistics strategy:
• Cost reduction (variable costs)
• Capital reduction (investment, fixed costs)
• Service Improvement (may be at odds with
the above two objectives).

3. Marketing
orientation
(competitive
advantage)
Time and
place utility
Efficient
movement to
customer
Proprietary
asset
Natural resources
(land, facilities,
and equipments)
Human resources
Financial resources
Information
resources
Management actions
Planning Implementation Control
Logistics Activities
•Customer Service
•Demand forecasting
•Distribution
communications
•Inventory control
•Material handling
•Order Processing
•Parts and service
support
•Plant and warehouse
site selection
•Procurement
•Packaging
•Return goods handling
•Salvage and scrap
disposal
•Traffic and
transportation
•Warehousing and
storage
Raw
materials
In-process
inventory
Finished
goods
Inputs into logistics
Suppliers
Logistics management
Customers
Outputs of
logistics
Components of
logistics management :

4. To gain a better grasp of the fundamental
trade-offs in logistics, I will divide logistics
activities into three categories:
Production
Storage
Transportation
The term “Resource” applies to all of the
factors of production, including
materials (e.g., Iron, fabric, parts),
equipment (e.g., machines or vehicles),
energy (e.g., oil, coal, electricity) and
labor.

5. PRODUCTION: Fundamental logistics questions are: (1) when should a
resource be produced; and (2) where should a resource be
produced.
The “when” question includes the topics of aggregate resource
planning, and production scheduling.
The “where” question includes the topics of facility location and
production allocation.
Some of the important production questions are:
(a) What outside source should be used to supply a part?
(b) Where should a new facility be built?
(c) When should a facility produce different items, taking into account:
• Seasonal demand patterns?
• Demand uncertainty?
• Cost of operating single, double, triple shifts?
• Labor costs?
(d) When should a firm use two or more sources for a part?

6. INVENTORY: Fundamental logistics questions are (1) when should a
resource (material, machine or labor) be put in inventory and taken
out of inventory; and (2) where should a resource be stored.
The “when” question includes the general topics of economic-order-
quantity models, safety stock models and seasonal models, and
specialized topics of fleet management, and personnel planning.
The “where” questions includes the topic of inventory echelons.
Some of the important inventory questions are:
(a) How much does it cost to store resources in inventory?
(b) How much “safety stock” should be carried in inventory to prevent
against running out of a resource?
(c) How much inventory should be carried in order to smooth out
seasonal variations in demand?
(d) Where should replacement parts be stored in multi-echelon
inventory system?

7. TRANSPORTATION: Fundamental logistics are: (1) where should
resources be moved to, and by what mode and route; (2) when
should resources be moved.
The “where” question includes the topics of terminal location,
vehicle routing, and shortest path methods and network flow
allocation.
The “when” question includes the topic of distribution rules.
Some of the important questions are:
(a) When should shipment be sent through terminals, and when
should shipment be sent direct?
(b) Which, and how many, terminals should shipments be sent
through?
(c) What are the best vehicle routes?
(d) When should a vehicle be dispatched over a route?

8. Logistics - Science of managing (controlling) the movement and
storage of goods (or people) from acquisition to consumption.
Goods: Raw Materials  Final products, and everything in between.
Logistics for services & people similar to goods logistics.
Ex. Police, fire, ambulance, passenger airlines and hotel
passengers (shuttle buss, taxi cabs, etc.
Movement = Transportation (between locations).
Storage = Inventory, Warehousing (at locations).
Difference between acquisition and consumption is a matter of space
and time.
NOTE: Logistics does not deal with Technology of Production, such
as the design of machines and vehicles and the design of finished
products.
Focus: Best way to overcome space and time that separates acquisition
and consumption.

9. 1998 CLM DEFINITION OF LOGISTICS
….is that part of the supply chain process that
plans, implements, and controls the efficient,
effective flow and storage of goods, services,
and related information from the point-of-
origin to the point-of-consumption in order to
meet customers' requirements.
Council of Logistics Management, 1998;
www.CLM1.org

10. Five Business Systems - Tightly Interconnected
Within The Organization
Measurement
Decisions
Management
Systems
Reward
Decisions
Strategic
Decisions
Transportation
Decisions
Sourcing
Decisions
Inventory
Decisions
Logistics
Systems
{
Price
Decisions
Promotion
Decisions
Marketing
Systems
Product
Decisions
Place (How,
where, how
much)
}
Production
Scheduling
Decisions
Production
Capacity
Decisions
Shop Floor
Decisions
Manufacturing
Systems
}
Product
Design
Decisions
Process
Design
Decisions Engineering
Systems
}
Copyright 2000 - All Rights Reserved

11. Logistics – Mission [A Bill of “Rights”]
• Logistics embodies the effort to deliver:
– the right product
– in the right quantity
– in the right condition
– to the right place
– at the right time
– for the right customer
– at the right cost

12. Activities and Logistics Decisions
Transportation
rate and contract negotiation
mode and service selection
routing and scheduling
Inventories
finished goods policies
supply scheduling
short term forecasting
Warehousing
private vs. public
space determination
warehouse configuration
Stock layout and dock design
stock placement
Cross-docking
Facility Location
determining location, number
and size of facilities
allocating demand to facilities
Customer Service
determining customer wants
determining customer response
to service changes
Materials Handling
equipment selection
equipment replacement
order picking procedures
Packaging design
Order Processing
order procedure determination
Production Scheduling
aggregate production quantities
sequencing and timing of
production runs

13. Logistics Planning
• Decide what, when, how in three levels:
– Strategic – long range > 1 year
– Tactical - < 1 year horizon
– Operational – frequently on hourly or daily basis
Examples of Decisions
Type Strategic Tactical Operational
Location
Transportation
Order Processing
(CS)
#Facilities, size,
location
Mode
Selecting order
entry system
Inventory
positioning
Seasonal Service
Mix
Priority rules for
customers
Routing
Replenishment Qty
and timing
Expediting orders

14. The Logistics (Strategic) Planning Triangle
Which mode?
Which carrier?
Which route?
Shipment size and
frequency?
Where?, How
many? What size?
Allocation?
Strategy/Control
system?
How much?
Where?

15. Transport Fundamentals
• Transport involves
– equipment (trucks, planes, trains, boats, pipeline),
– people (drivers, loaders & un-loaders), and
– decisions (routing, timing, quantities, equipment size,
transport mode).
When deciding the transport mode for a given product
there are several things to consider:
• Mode price
• Transit time and variability (reliability)
• Potential for loss or damage.
NOTE: In developing countries we often find it necessary to
locate production close to both markets and resources,
while in countries with developed distribution systems people
can live in places far from production and resources.
Most important component of logistics cost.
Usually 1/3 - 2/3 of total cost.

16. Routes of Goods
Goods at
shippers
Freight
forwarder
warehouse
Air
terminal
plane
air
Freight
forwarder
warehouse
Goods at
consignees
Container
terminal
vessel
sea May
change
transpor-
tation
modes
truck
land
railway
land barge
mid-stream
pier
bulk goods
sea
let us guess

17. Air
•Rapidly growing segment of transportation industry
•Lightweight, small items [Products: Perishable and time
sensitive goods: Flowers, produce, electronics, mail, emergency
shipments, documents, etc.]
•Quick, reliable, expensive
•Often combined with trucking operations
Rail
•Low cost, high-volume [Products: Heavy industry, minerals,
chemicals, agricultural products, autos, etc.]
•Improving flexibility
•intermodal service
Truck
•Most used mode
•Flexible, small loads [Products: Medium and light
manufacturing, food, clothing, all retail goods]
•Trucks can go door-to-door as opposed to planes and trains.
Single-mode Service Choices and Issues

18. Water
•One of oldest means of transport
•Low-cost, high-volume, slow
•Bulky, heavy and/or large items (Products: Nonperishable
bulk cargo - Liquids, minerals, grain, petroleum, lumber,
etc )]
•Standardized shipping containers improve service
•Combined with trucking & rail for complete systems
•International trade
Pipeline
•Primarily for oil & refined oil products
•Slurry lines carry coal or kaolin
•High capital investment
•Low operating costs
•Can cross difficult terrain
•Highly reliable; Low product losses
Single-mode Service Choices and Issues (Contd.)

19. Transport Cost Characteristics
– Fixed costs:
• Terminal facilities
• Transport equipment
• Carrier administration
• Roadway acquisition and maintenance
[Infrastructure (road, rail, pipeline,
navigation, etc.)]
– Variable costs:
• Fuel
• Labor
• Equipment maintenance
• Handling, pickup & delivery, taxes
NOTE: Cost structure varies by mode

20. Transport Cost Characteristics
• Rail
– High fixed costs, low variable costs
– High volumes result in lower per unit (variable) costs
• Highway
– Lower fixed costs (don’t need to own or maintain roads)
– Higher unit costs than rail due to lower capacity per truck
– Terminal expenses and line-haul expenses
• Water
– High terminal (port) costs and high equipment costs (both fixed)
– Very low unit costs
• Air
– Substantial fixed costs
– Variable costs depend highly on distance traveled
• Pipeline
– Highest proportion of fixed cost of any mode due to pipeline
ownership and maintenance and extremely low variable costs

21. Vehicle Routing:
- Separate single origin and destination:
Once we have selected a transport mode and have
goods that need to go from point A to point B, we
must decide how to route a vehicle (or vehicles)
from point A to point B.
Given a map of all of our route choices between A and
B we can create a network representing these
choices The problem then reduces to the problem of
finding the shortest path in the network from point
A to B.
This is a well solved problem that can use Dijkstra’s
Algorithm for quick solution of small to medium
(several thousand nodes) sized problems.

22. Suppose we have multiple sources and multiple
destinations, that each destination requires some integer
number of truckloads, and that none of the sources have
capacity restrictions [No Capacity Restriction].
In this case we can simply apply the transportation method
of linear programming to determine the assignment of
sources to destinations.
Sources Destinations
Vehicle Routing:
- Multiple Origin and Destination Points

23. - Coincident Origin and Destination: The TSP
• If a vehicle must deliver to more than two customers, we
must decide the order in which we will visit those customers
so as to minimize the total cost of making the delivery.
• We first suppose that any time that we make a delivery to
customers we are able to make use of only a single vehicle,
i.e., that vehicle capacity of our only truck is never an issue.
• In this case, we need to dispatch a single vehicle from our
depot to n - 1 customers, with the vehicle returning to the
depot following its final delivery.
• This is the well-known Traveling Salesman Problem (TSP).
The TSP has been well studied and solved for problem
instances involving thousands of nodes. We can formulate the
TSP as follows:
Vehicle Routing:

24. TSP Formulation
– Minimize
– Subject to:
c x
ij ij
j J
i I 



x i I
x j J
x U U N
x i I j J
ij
j J
ij
i I
ij
i j E U
ij






  
  
   
   
1
1
1
,
,
,
{0,1},
( , ) ( )
,
In the TSP formulation if we remove the third constraint set we
have the simple assignment problem, which can be easily
solved.
The addition of the third constraint set, commonly called sub-
tour elimination constraints, makes this a very difficult problem
to solve.

25. Questions about the TSP
• Given a problem with n nodes, how many distinct
feasible tours exist?
• How many arcs will the network have?
• How many xij variables will we have?
• How could we quantify the number of subtour
elimination constraints?
• The complexity of the TSP has led to several heuristic
or approximate methods for finding good feasible
solutions. The simplest solution we might think of is
that of the nearest neighbor.

26. Vehicle Routing: TSP, inventory routing, and vehicle routing
• Traveling Salesman Problem (TSP): salesman visits n cities at
minimum cost
• vehicle routing problem (VRP): m vehicles with capacity to
deliver to n customers who have volume requirement, time
windows, etc.
• Inventory Routing: m vehicle to delivery to n customer with
time windows, vehicle and storage capacity constraints, and un-
specificed amount to be delivered.
• Heuristics
1. Load points closest together on the same truck
2. Build routes starting with points farther from depot first
3. Fill the largest vehicle to capacity first
4. Routes should not cross
5. Form teardrop pattern routes.
6. Plan pickups during deliveries, not after all deliveries have
been made.

27. Illustration of VRP
(Outlier)
Depot
50
76
39
112
88
29
123
44
58
90
77
89
57
115
124
59 176
65
98 125
Truck Capacity = 250
What is the minimum # of trucks we would need? Maximum?

28. Vehicle Routing
• Find best vehicle route(s) to serve a set of orders
from customers.
• Best route may be
– minimum cost,
– minimum distance, or
– minimum travel time.
• Orders may be
– Delivery from depot to customer.
– Pickup at customer and return to depot.
– Pickup at one place and deliver to another
place.

29. Complications
• Multiple vehicle types.
• Multiple vehicle capacities.
– Weight, Cubic feet, Floor space, Value.
• Many Costs:
– Fixed charge.
– Variable costs per loaded mile & per empty mile.
– Waiting time; Layover time.
– Cost per stop (handling).
– Loading and unloading cost.
• Priorities for customers or orders.
–Pure Pickup or Delivery Problems.
–Mixed Pickups and Deliveries.
–Pickup-Delivery Problems.
–Backhauls

30. More Complications
• Time windows for pickup and delivery.
– Hard vs. soft
• Compatibility
– Vehicles and customers.
– Vehicles and orders.
– Order types.
– Drivers and vehicles.
• Driver rules (DOT)
– Max drive duration = 10 hrs. before 8 hr. break.
– Max work duration = 15 hrs. before 8 hr break.
– Max trip duration = 144 hrs.

31. Simple Models
• Homogeneous vehicles.
• One capacity (weight or volume).
• Minimize distance.
• No time windows or one time window per
customer.
• No compatibility constraints.
• No DOT rules.

32. VRP Solutions
• Heuristics
– Construction: build a feasible route.
– Improvement: improve a feasible route.
• Not necessarily optimal, but fast.
• Performance depends on problem.
• Worst case performance may be very poor.
• Exact algorithms
– Integer programming.
– Branch and bound.
• Optimal, but usually slow and applicable for small size
problem
• Difficult to include complications.

33. The VRP is applicable in many practical situations directly related to
 the physical delivery of goods such as
 distribution of petroleum products,
 distribution of industrial gases,
 newspaper deliveries,
 delivery of goods to retail store,
 garbage collection and disposal,
 package pick-up and delivery,
 milk pick-up and delivery, etc.
 the non-movement of goods such as
 picking up of students by school buses,
 routing of salesmen,
 reading of electric meters,
 preventive maintenance inspection tours,
 employee pick-up and drop-off , etc.
APPLICATIONS OF VRP

34.  A DSS
 Employee Bus Routing
 Commodity Distribution
 In COVERS
 Efficient Heuristic Procedures
 NNH
 MNNH
 MSCWH
 Simulation Features
 Manipulate the System Generated Routes
 Completely User Generated Routes
 COVERS Handles
 Multi-Depot VRP
 Heterogeneous VRP
COVERS- COMPUTERIZED VEHICLE ROUTING SYSTEM

35. EMPLOYEE PICKUP VEHICLE ROUTING PROBLEM (EPVRP) –
BANGALORE, KARNATAKA, INDIA
 Indian Telephone Industries [ITI] Limited
 Bharat Electronics Limited [BEL]
 Hindustan Machine Tools [HMT]
 Hindustan Aeronautics Limited [HAL]
 Indian Space Research Organization [ISRO]
 National Aeronautical Laboratory [NAL]
 Central Machine Tools of India [CMTI]
 ………

36. AS A PROBLEM IN OR, A SIMPLIFIED EPVRP CAN BE DESCRIBED AS FOLLOWS:
GIVEN
 A set (fixed number) of pick-up or delivery points,
 The demand at every pick-up or delivery points (deterministic),
 A set (fixed number) of vehicles (homogeneous) and
 All relevant distance information across pick-up points.
IT IS REQUIRED TO FIND AN EFFECTIVE/EFFICIENT SOLUTION FOR
 Assigning pick-up points to vehicles and
 Sequencing pick-up points on the route of each vehicle
SO AS TO ACHIEVE THE OBJECTIVE OF
 Minimizing the total distance traveled by the vehicles and/or the number of vehicles
used.
UNDER THE CONSTRAINTS THAT
 Every route originates and terminates at the depot
 The capacity of vehicle is restricted
 The maximum distance (time) allowed for a vehicle on any route is within a pre-
specified limit
 Each pick-up point is visited once only
 Etc.,

37. AN ILP FORMULATION - EPVRP
Source : WATERS (1998) 
ASSUMPTIONS
 Vehicle capacity is known and constant (homogenous)
 The number of vehicles available is known (at least the minimum
number of vehicles required is known)
 The demand at every pick-up point is known (deterministic)
 Maximum distance to be traveled by each vehicle is known and
constant for all vehicles
 Demand at every pick-up point is less than or equal to vehicle
capacity
 Every pick-up point is served by only one vehicle
Further, keeping in line with Water’s formulation, the model formulation is
oriented towards routing during drop-back rather than pick-up. It is assumed
that the reverse logic holds good for pick-up.
 Expanding the Scope of Linear Programming Solutions for Vehicle
Scheduling Problems. OMEGA, 16(6), 577-583

38. COMPUTATIONAL COMPLEXITY - OPTIMAL SOLUTION
#
PUP
Tot
Quantities
(Units)
# Variables
Including (0, 1)
Variables
# (0, 1)
Variables
#
Constraints
Optimal
Distance
(Km.)
# Routes # Iterations
(LINDO)
CPU Time
(AT 486)
4 61 48 16 60 13.2 1 45 2
5 71 75 25 85 26.4 2 330 3
6 79 108 36 114 28.6 2 353 6
7 106 147 49 147 31.0 2 2780 23
8 117 192 64 187 31.0 2 70724 80
9 132 243 81 225 37.4 2 43021 667
(11 Mts)
10 137 300 100 270 47.8 3 4963340 100800
(28 Hrs.)
Sutcliffe and Board (1990) estimated that a simple extrapolation of Waters’ (1988) ILP approach using
the SCICONIC software might take nearly 1,20,000 years of CPU time on a VAX 8600 machine to solve a
VRP with 38 pick-up points!
 Optimal Solution of VRP: Transporting Mentally Handicapped Adults to an Adult Training Center. JORS, 41(1), 61-67.

39.  Nearest Insertion Heuristic (NIH)
 Cheapest Insertion Heuristic (CIH)
 Parallel Version of Clarke & Wright Heuristic (PCWH)
 Sequential Version of Clarke & Wright Heuristic (SCWH)
 Convex Hull Heuristic (CHH)
 Nearest Neighbour Heuristic (NHH)
 Modified NNH (MNNH)
 Modified SCWH 1 (MSCWH-1)
 Modified SCWH 2 (MSCWH-2)
HEURISTIC ALGORITHMS

40. CASE STUDY : DETAILS OF ROUTES, DISTANCES & SEAT UTILIZATION
Shift Timings #
Commuters
# Pickup
Points
#
Routes
Total Distance
per Trip (Km.)
Seat
Utilization (%)
A 06.15 – 02.15 PM 3659 303 64 1977.0 89.0
FG 07.30 – 04.15 PM 3999 313 66 2163.0 94.3
AG 08.45 – 05.30 PM 3042 286 53 1808.3 90.0
B 02.15 – 10.15 PM 975 242 30 1056.7 54.0
C  10.15 – 06.15 AM 40 ---- ---- ---- ----
Total 11715 410 213+
(426)
7005.0 
(14010)
----
 Ignored in our study
 Each Bus Route (Trip) Repeated; Two Trips a day, Once for Pick-up and once for Drop-off.
 Distinct Pick-up Points

41. COMPARATIVE PERFORMANCE (CASE STUDY) – TOTAL DISTANCE
Procedures Shift – 1
A
Shift – 2
FG
Shift – 3
AG
Shift – 4
B
Total Distance
(Km.)
Savings
(in %)
CPU Time
PC/AT – 486
@ 33 MHz
(Minutes)
Existing
Practice
(Manual)
1977.0 2163.0 1808.3 1056.7 7005.0 ----- ----
NIH 1875.8 2047.7 1734.1 890.3 6547.9 6.5 12
CIH 2155.2 2322.3 1914.2 1020.7 7412.4 - 5.8 52
PCWH 1803.5 2026.1 1761.1 1080.9 6671.6 4.76 19
SCWH 2139.2 2306.6 1889.2 1014.5 7349.5 - 4.9 18
CHH 1903.8 2047.7 1749.2 964.7 6665.4 4.85 55
NNH 1822.9 2063.2 1708.0 900.0 6494.1 7.29 1
MNNH 1817.7 2040.8 1740.7 858.9 6458.1 7.81 1
MSCWH-1 1796.2 2066.4 1687.5 910.2 6460.3 7.78 2
MSCWH-2 1799.4 2047.0 1688.5 908.5 6443.4 8.02 2
(Figures in Table represent travel distance in Km. For Pick-up only)

42. COMPARATIVE PERFORMANCE (CASE STUDY) – TOTAL NUMBER ROUTES
Procedures Shift – 1
A
Shift – 2
FG
Shift – 3
AG
Shift – 4
B
Total Routes Reduction in
Trips (%)
Existing
Practice
(Manual)
64 66 53 30 213 -----
NIH 60 63 51 23 197 7.51
CIH 65 69 52 27 213 0
PCWH 63 68 56 36 223 - 4.7
SCWH 65 70 55 28 218 - 2.3
CHH 60 62 51 25 198 7.04
NNH 57 64 50 24 195 8.45
MNNH 57 63 51 23 194 8.92
MSCWH-1 58 63 49 24 195 8.45
MSCWH-2 58 63 49 24 194 8.92
Figures in Table represent number of trips for Pick-up only

43.  Nearest Neighbour Heuristic (NHH)
 Modified NNH (MNNH)
 Modified SCWH-2 (MSCWH-2)
HEURISTIC ALGORITHMS - DSS IMPLEMENTATION

44. A Schematic Diagram of COVERS
DATA MANAGEMENT MODULE
 General file
 Depot Data File
 Vehicle Data File
 Pickup point Demand Data File
 Inter-Stop Distance Data File
MODEL MANAGEMENT MODULE
 Heuristic Procedures
 Simulation Model
REPORT MANAGEMENT MODULE
 Details of Route Sequence
 Summary of Routes
 Overall Summary of Routes
 Depot wise Route Allocation
 Vehicle Type wise Route Allocation
CONTROL MODULE
COMPUTER SYSTEM
USER