Stochastic Linear Programming Algorithms: A Comparison Based on a Model Management System

by Janos Mayer

0 ratings • 0 reviews • 0 shelved
Book cover for Stochastic Linear Programming Algorithms

Bookhype may earn a small commission from qualifying purchases. Full disclosure.

A computationally oriented comparison of solution algorithms for two stage and jointly chance constrained stochastic linear programming problems, this is the first book to present comparative computational results with several major stochastic programming solution approaches.

The following methods are considered: regularized decomposition, stochastic decomposition and successive discrete approximation methods for two stage problems; cutting plane methods, and a reduced gradient method for jointly chance constrained problems.

The first part of the book introduces the algorithms, including a unified approach to decomposition methods and their regularized counterparts. The second part addresses computer implementation of the methods, describes a testing environment based on a model management system, and presents comparative computational results with the various algorithms. Emphasis is on the computational behavior of the algorithms.

  • ISBN10 9056991442
  • ISBN13 9789056991449
  • Publish Date 25 February 1998
  • Publish Status Active
  • Publish Country GB
  • Imprint Taylor & Francis Ltd
  • Format Hardcover
  • Pages 163
  • Language English