Computational Mathematical Programming
Elsevier (Publisher)
Published in August 1987
Book
Paperback/Softback
200 pages
978-0-444-70309-5 (ISBN)
Description
As modelling efforts attempt to solve problems related to ever more complex systems, and as algorithms are developed specifically to handle problems having thousands (or even hundreds of thousands) of variables, the need for sound computational testing and full disclosure of experimental results is both obvious and immediate. This collection of papers reflects both the current technology available to mathematical programmers for solving optimization problems, and mechanisms for testing and determining the quality of software used. This testing requires suitable test problems and the execution of a designed experiment to determine the efficiency, robustness, reliability and applicability of various algorithms. Many aspects of computational mathematical programming are covered: the testing of new algorithms for optimizing functions of a specified form, computational comparisons of known algorithms, a preliminary computational evaluation of the new projective method, why decomposition methods have not been as successful as originally anticipated, etc.
As modelling efforts attempt to solve problems related to ever more complex systems, and as algorithms are developed specifically to handle problems having thousands (or even hundreds of thousands) of variables, the need for sound computational testing and full disclosure of experimental results is both obvious and immediate. This collection of papers reflects both the current technology available to mathematical programmers for solving optimization problems, and mechanisms for testing and determining the quality of software used. This testing requires suitable test problems and the execution of a designed experiment to determine the efficiency, robustness, reliability and applicability of various algorithms. Many aspects of computational mathematical programming are covered: the testing of new algorithms for optimizing functions of a specified form, computational comparisons of known algorithms, a preliminary computational evaluation of the new projective method, why decomposition methods have not been as successful as originally anticipated, etc.
As modelling efforts attempt to solve problems related to ever more complex systems, and as algorithms are developed specifically to handle problems having thousands (or even hundreds of thousands) of variables, the need for sound computational testing and full disclosure of experimental results is both obvious and immediate. This collection of papers reflects both the current technology available to mathematical programmers for solving optimization problems, and mechanisms for testing and determining the quality of software used. This testing requires suitable test problems and the execution of a designed experiment to determine the efficiency, robustness, reliability and applicability of various algorithms. Many aspects of computational mathematical programming are covered: the testing of new algorithms for optimizing functions of a specified form, computational comparisons of known algorithms, a preliminary computational evaluation of the new projective method, why decomposition methods have not been as successful as originally anticipated, etc.
More details
Series
Language
English
Place of publication
Oxford
United Kingdom
Publishing group
Elsevier Science & Technology
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 240 mm
Width: 160 mm
ISBN-13
978-0-444-70309-5 (9780444703095)
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Schweitzer Classification
Content
An Implicit Enumeration Procedure for the General Linear Complementarity Problem (F. Al-Khayyal). Recursive Quadratic Programming Methods Based on the Augmented Lagrangian (M.C. Bartholomew-Biggs). A Primal Truncated Newton Algorithm with Application to Large-Scale Nonlinear Network Optimization (R.S. Dembo). Approximating Some Convex Programs in Terms of Borel Fields. Computer-Assisted Analysis for Diagnosing Infeasible or Unbounded Linear Programs (H.J. Greenberg). Restricted Simplicial Decomposition: Computation and Extensions (D.W. Hearn, S. Lawphongpanich and J.A. Ventura). Recent Advances in the Decomposition Approach to Linear Programming (J.K. Ho). A Note on Solution of Nonlinear Programming Problems with Imprecise Function and Gradient Values (M. Kupferschmid and J.G. Ecker). A New Algorithm for Highly Curved Constrained Optimization (Z.A. Maany). An Implementation of an Algorithm for Univariate Minimization and an Application to Nested Optimization (R. Mifflin). On Practical Stopping Rules for the Simplex Method (W. Ogryczak). An Experimental Approach to Karmarkar's Projective Method for Linear Programming (J.A. Tomlin).