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1. Convex and Quadratic Programming.- 1.1 Introduction.- 1.1.1 The Linearization Algorithm.- 1.1.2 Convergence of the Algorithm.- 1.1.3 General Remarks.- 1.1.4 Notation.- 1.2 …
For a long time the techniques of solving linear optimization (LP) problems improved only marginally. Fifteen years ago, however, a revolutionary discovery changed everything. A …
In Linear Programming: A Modern Integrated Analysis, both boundary (simplex) and interior point methods are derived from the complementary slackness theorem and, unlike most …
This book focuses largely on constrained optimization. It begins with a substantial treatment of linear programming and proceeds to convex analysis, network flows, integer …