Description

Book Synopsis

The conical approach provides a geometrical understanding of optimization and is a powerful research tool and useful problem-solving technique (for example, in decision support and real time control applications).
Conical optimality conditions are first stated in a very general optimization framework, and then applied to linear programming. A complete theory along with primal and dual algorithms is given, and solutions and algorithms are also provided for vector and robust linear optimization. The advantages of parameter dependence of conical methods are fully discussed. In addition to numerical results, the book provides source codes and detailed documentation of a Modula-2 implementation for the main algorithms.



Table of Contents

Part I: General Theory
Part II: Further Advanced Results
Part III: Implementations and Numerical Results

Conical Approach to Linear Programming

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    A Hardback by P D'Alessandro

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      Book details

      Publisher Taylor & Francis
      Imprint Taylor & Francis Ltd
      Published 29 October 1997
      ISBN-13 9789056990312
      978-9056990312
      ISBN-10 9056990314
      Also in:
      Algorithms and data structures Computer science Geometry

      Description

      Book Synopsis

      The conical approach provides a geometrical understanding of optimization and is a powerful research tool and useful problem-solving technique (for example, in decision support and real time control applications).
      Conical optimality conditions are first stated in a very general optimization framework, and then applied to linear programming. A complete theory along with primal and dual algorithms is given, and solutions and algorithms are also provided for vector and robust linear optimization. The advantages of parameter dependence of conical methods are fully discussed. In addition to numerical results, the book provides source codes and detailed documentation of a Modula-2 implementation for the main algorithms.



      Table of Contents

      Part I: General Theory
      Part II: Further Advanced Results
      Part III: Implementations and Numerical Results

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