Linear Programming - University of Kentucky

The Role of Mathematical Models in OperationsDecision Making B2 Constrained Optimization Models B2 Advantages and Disadvantages of Using Optimiza-tion Models B5 Assumptions of Linear Programming Models B6 Formulating Linear Programs B7 The Geometry of Linear Programs B14 The Graphical Solution Approach B15 The Simplex Algorithm B17 Using Artificial Variables B26 Computer Solutions of Linear Programs B29 Using Linear Programming Models for DecisionMaking B32 Before 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 14 Linear ProgrammingSUPPLEMENTBLEARNING OBJECTIVESA fter 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.

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 a good production plan? We need to specify a criterion for evaluation—an objective func-tion. The most appropriate objective function is to maximize monthly profit. (Actually, this

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