1. Introduction

2. MS / OR Definition: Management Science (MS) or Operations Research (OR) is the scientific discipline devoted to the analysis and solution of complex decision making problems. Management science The discipline of applying advanced analytical methods to help make better decisions. Devoted to solving managerial-type problems using quantitative models

3. The Management Science Approach Management science is a scientific approach to solving management problems. It is used in a variety of organizations to solve many different types of problems. It encompasses a logical mathematical approach to problem solving. Management science, also known as operations research, quantitative methods, etc., involves a philosophy of problem solving in a logical manner.

4. Application Areas Applications of management science Forecasting, capital budgeting, portfolio analysis, capacity planning, scheduling, marketing, inventory management, project management, and production planning.

5. The Management Science Process Figure: The management science process

6. Steps in the Management Science Process  Observation - Identification of a problem that exists (or may occur soon) in a system or organization.  Definition of the Problem - problem must be clearly and consistently defined, showing its boundaries and interactions with the objectives of the organization.  Model Construction - Development of the functional mathematical relationships that describe the decision variables, objective function and constraints of the problem.  Model Solution - Models solved using management science techniques.  Model Implementation - Actual use of the model or its solution.

7. MAX (MIN): f 0 (X 1, X 2, …, X n ) S.T. f 1 (X 1, X 2, …, X n )<=b 1 : f k (X 1, X 2, …, X n )>=b k : f m (X 1, X 2, …, X n )=b m Modeling & Formulation

8. Optimization Models Optimization Models We have to satisfy our Objective Constraints and Constrained Optimization Realize objective: (maximize profit…minimize cost) Subject to limitations (constraints) Time-Budget-Space-Capacity-Energy-Demand- Material Results: Optimal Decisions

9. Information and Data:  Business firm makes and sells a steel product  Product costs $5 to produce  Product sells for $20  Product requires 4 pounds of steel to make  Firm has 100 pounds of steel Business Problem:  Determine the number of units to produce to make the most profit, given the limited amount of steel available. Example of Model Construction (1 of 3)

10. Variables:x = # units to produce (decision variable) Z = total profit (in $) Model:Z = $20x - $5x (objective function) 4x = 100 lb of steel (resource constraint) Parameters:$20, $5, 4 lbs, 100 lbs (known values) Formal Specification of Model: maximize Z = $15x subject to 4x = 100 Example of Model Construction (2 of 3)

11. Example of Model Construction (3 of 3) Solve the constraint equation: 4x = 100 (4x)/4 = (100)/4 x = 25 units Substitute this value into the profit function: Z = $15x = (15)(25) = $375 (Produce 25 units, to yield a profit of $375) Model Solution:

12. Additional Information and Data:  Now suppose that there is a second product, y, that has a profit of $10 and requires 2 pounds of steel to make (in addition to the example considered earlier). Business Problem:  Determine the number of units of x and y to produce to make the most profit, given the limited amount of steel available. Additional Example of Model Construction

13. New Model: Maximize Z = 15 x + 10 y Subject to 4 x + 2 y = 100 x, y >= 0