3. INTRODUCTION
Definition:
Computer-based information system.
Supports business or organizational decision-making
activities.
DSSs serve the management, operations, and planning
levels of an organization.
4. INTRODUCTION
What is a decision?
Decision is a choice from two or more alternatives.
Is the first part of problem solving exercise.
Two types:
Programmed.
Non programmed.
5.
6.
7. DSS helps in decision making.
DSSs include knowledge-based systems.
Can be used to validate the decision by performing
sensitivity analysis on various parameter of the
problem.
8. CHARACTERISTICS
Handle large amounts of data from different
sources.
Provide report and presentation flexibility.
Offer both textual and graphical orientation.
Support drill-down analysis.
Perform complex, sophisticated analysis and
comparisons using advanced software packages.
9. COMPONENTS
Database management system (DBMS).
Model-base management system (MBMS).
Dialog generation and management system
(DGMS).
10.
11. TYPE OF TOOLS/MODELS
Behavioral models.
Management science models.
Operations research (OR) models .
12. LINEAR PROGRAMMING: MATHEMATICAL MODEL
Linear programming (LP, or linear optimization) is a
mathematical method for determining a way to
achieve the best outcome.
Tool used in operational model.
Used to make the best possible decision under
given constraints.
13. LINEAR PROGRAMMING: MATHEMATICAL MODEL
Assumptions made:
Proportionality
No extra startup charge at the beginning.
Additivity
Divisibility
14. A calculator company produces a scientific
calculator and a graphing calculator. Long-term
projections indicate an expected demand of at least
100 scientific and 80 graphing calculators each day.
Because of limitations on production capacity, no
more than 200 scientific and 170 graphing
calculators can be made daily. To satisfy a shipping
contract, a total of at least 200 calculators much be
shipped each day. If each scientific calculator sold
results in a $2 loss, but each graphing calculator
produces a $5 profit, how many of each type should
be made daily to maximize net profits?
15. x: number of scientific calculators produced
y: number of graphing calculators produced
two constraints, x > 0 and y > 0.
x > 100 and y > 80.
The exercise also gives maximums: x < 200 and y
< 170.
16. The minimum shipping requirement gives
x + y > 200; in other words, y > –x + 200
R = –2x + 5y, subject to :
100 < x < 200
80 < y < 170
y > –x + 200
To optimize
17.
18. ADVANTAGES
Time savings
Enhance effectiveness
Improve interpersonal communication
Cost reduction
A decision support system (DSS) is a computer-based information system that supports business or organizational decision-making activities. DSSs serve the management, operations, and planning levels of an organization and help to make decisions, which may be rapidly changing and not easily specified in advance.DSSs include knowledge-based systems. A properly designed DSS is an interactive software-based system intended to help decision makers compile useful information from a combination of raw data, documents, personal knowledge, or business models to identify and solve problems and make decisions.
Basically “decision is a choice from two or more alternatives” like deciding which dress to wear or what profession to take up. Decision implies the end of deliberation and beginning of action. Risk is indispensible part of decision making.Programmed : • Decision made using a rule, procedure, or quantitative method• Easy to computerize using traditional information systemsNon programmed decisions• Decision that deals with unusual or exceptional situations• Not easily quantifiable
The decision support system basically helps the information system in the intelligence phase where the objective is to identify the problem and then go to the design phase for solution. The choice of selection criterion varies from problem to problem. It is therefore, required to go through these phases again and again till a satisfactory solution is found. In the following three phase cycle, you may use inquiry, analysis, and models or accounting system to come to a rational solution. These systems can be used to validate the decision by performing sensitivity analysis on various parameter of the problem.
Database management system (DBMS). A DBMS serves as a data bank for the DSS. It stores large quantities of data that are relevant to the class of problems for which the DSS has been designed and provides logical data structures (as opposed to the physical data structures) with which the users interact. A DBMS separates the users from the physical aspects of the database structure and processing. It should also be capable of informing the user of the types of data that are available and how to gain access to them. • Model-base management system (MBMS). The role of MBMS is analogous to that of a DBMS. Its primary function is providing independence between specific models that are used in a DSS from the applications that use them. The purpose of an MBMS is to transform data from the DBMS into information that is useful in decision making. Since many problems that the user of a DSS will cope with may be unstructured, the MBMS should also be capable of assisting the user in model building. • Dialog generation and management system (DGMS). The main product of an interaction with a DSS is insight. As their users are often managers who are not computer-trained, DSSs need to be equipped with intuitive and easy-to-use interfaces. These interfaces aid in model building, but also in interaction with the model, such as gaining insight and recommendations from it. The primary responsibility of a DGMS is to enhance the ability of the system user to utilize and benefit from the DSS. In the remainder of this article, we will use the broader term user interface rather than DGMS.
Behavioral models These models are useful in understanding the behavior amongst the business variables. The decision maker can then make decisions giving due regard to such behavioral relationships. The trend analysis, forecasting, and the statistical analysis models belong to this category. The trend analysis indicates how different variable behave in trend setting in the past and hence in the future. A regression models shows the correlation between one or more variables. It also helps in identifying the influence of one variable on the other. These types of models are largely used in process control, manufacturing, agricultural sciences, medicines, psychology and marketing. The behavioral analysis can be used to set the points for alert, alarm and action for the decision maker. Management science models These models are developed on the principles of business management, accounting and econometrics. In many areas of management, the proven methods of management control are available which can be used for the management decision. There are also several management systems, which can be converted into the decision support system models. For example, the budgetary systems, the cost accounting systems, the system of capital budgeting for better return on the investment, the ABC analysis, the control of inventory through the maximum-minimum levels, the MRP system, etc., are the examples of the use of the management science in the materials management. Production planning and control scheduling and loading systems are the examples in Production Management. Manpower planning and forecasting is the example in Personnel Management. Some of these models can be used straight away in the design of the decision support system. While some others require the use of management principles and practices, most of the procedure based decision making models belong to this category. One can develop a model for selection of vendor for procurement of an item, based on the complex logical information scrutiny. Such models take away the personal bias of the decision maker.Operations research (OR) models The Operations Research (OR) models are mathematical models. These models. These models represent a real life problem situation in terms of the variables, constants and parameters expressed in algebraic equations. Since, the models are mathematical; there is solution to these problems. In arriving the solution, methods of calculus, matrix algebra, probability, and set theory are used. These models have clarity to the extent that each of them has a set of assumptions which must be true in real life. Further, if the assumptions are valid, the solutions offered are realistic and practical; the model represents the real life problem situation
Linear programming (LP, or linear optimization) is a mathematical method for determining a way to achieve the best outcome (such as maximum profit or lowest cost) in a given mathematical model for some list of requirements represented as linear relationships. Linear programming is a specific case of mathematical programming (mathematical optimization).More formally, linear programming is a technique for the optimization of a linear objective function, subject to linear equality and linear inequality constraints. Its feasible region is a convex polyhedron, which is a set defined as the intersection of finitely many half spaces, each of which is defined by a linear inequality. Its objective function is a real-valued affine function defined on this polyhedron. A linear programming algorithm finds a point in the polyhedron where this function has the smallest (or largest) value if such point exists This model is applicable where the decision variables assume the values which are non-zero, and the relationship among the various variables is linear. There are limitations, called constraints to use the variables or the combination thereof.
Refer textbook pg 442
The question asks for the optimal number of calculators, so my variables will stand for that:Since they can't produce negative numbers of calculators, I have the two constraints
http://www.purplemath.com/modules/linprog3.htmSee the problem on this page
