By Saul I. Gass

Pleasing, nontechnical creation covers simple thoughts of linear programming and its dating to operations study; geometric interpretation and challenge fixing, resolution options, community difficulties, even more. Appendix bargains targeted statements of definitions, theorems, and strategies, extra computational tactics. in simple terms high-school algebra wanted. Bibliography.

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Extra resources for An Illustrated Guide to Linear Programming

Example text

Meta-Recipe Revisited . . . . . . . . . . . . . . . . . . . . . Problem Formulation . . . . . . . . . . . . . . . . . . . . . . Decomposition of the Solution Set . . . . . . . . . . . . . . . Principle of Conditional Optimization . . . . . . . . . . . . . Conditional Problems . . . . . . . . . . . . . . . . . . . . . . Optimality Equation .

The Role of a Decomposition Scheme . . . . . . . . . . . . . . Dynamic Programming Problem — Revisited . . . . . . . . . Trivial Decomposition Scheme . . . . . . . . . . . . . . . . . Summary and a Look Ahead . . . . . . . . . . . . . . . . . . 1 Dynamic Programming Introduction The conceptual dimension of dynamic programming consists of a cluster of ideas whose profound simplicity presents the dynamic programming scholar setting out to elucidate them with a difficult task.

Optimality Equation . . . . . . . . . . . . . . . . . . . . . . Solution Procedure . . . . . . . . . . . . . . . . . . . . . . . Time Out: Direct Enumeration! . . . . . . . . . . . . . . . . Equivalent Conditional Problems . . . . . . . . . . . . . . . . Modified Problems . . . . . . . . . . . . . . . . . . . . . . . The Role of a Decomposition Scheme . . . . . . . . . . .

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