Linear Programming

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The Role of Mathematical Models in OperationsDecision Making B2Constrained Optimization Models B2Advantages and Disadvantages of Using Optimiza-tion Models B5Assumptions of Linear Programming Models B6Formulating Linear Programs B7The Geometry of Linear Programs B14The Graphical Solution Approach B15The Simplex Algorithm B17Using Artificial Variables B26Computer Solutions of Linear Programs B29Using Linear Programming Models for DecisionMaking B32Before studying this supplement you should know or, if necessary, review1. Competitive priorities, Chapter 22. Capacity management concepts, Chapter 93. Aggregate planning, Chapter 134. Developing a master schedule, Chapter 14Linear ProgrammingSUPPLEMENTBLEARNING OBJECTIVESAfter studying this supplement, you should be able toDescribe the role of mathematical models in operations decision constrained optimization the advantages and disadvantages ofusing optimization the assumptions of Linear Linear the geometry of Linear the graphical solution the simplex artificial computer solutions of Linear Linear Programming models for decisionmaking.

Objective function.Any pair of numerical values for the variables M and Y is a produc- tion plan. For example,M 10,000 and Y 20,000 means we make 10,000 packages of Meaties and 20,000 packages of Yummies each month. But how do we know whether this is

  Programming, Linear programming, Linear, Variable