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   Book Info

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Handbook of Applied Optimization  
Author: P. M. Pardalos (Editor), et al
ISBN: 0195125940
Format: Handover
Publish Date: June, 2005
 
     
     
   Book Review


From Book News, Inc.
This reference provides a guide for applications specialists to the most important instruments and the major recent advances in the field of applied optimization. Pardalos (industrial and systems engineering, U. of Florida) and Resende (research scientist, AT&T Laboratories) present 26 chapters in which expert contributors discuss algorithms (linear, semidefinite, quadratic, nonlinear, stochastic, and integer programming), combinatorial optimization, deterministic global optimization, decomposition methods for mathematical programming, network and hierarchical optimization, artificial neural networks and parallel algorithms in optimization, complementary and related problems, data envelopment analysis, and randomization in discrete optimization. They also cover applications (problem types, application areas) and software.Copyright © 2004 Book News, Inc., Portland, OR


Book Info
Comprehensive resource brings together in one volume the major advances in the field. Covers the optimization problems in a wide range of settings, from the airline and aerospace industries to telecommunications, finance, health systems, biomedicine, and engineering.




Handbook of Applied Optimization

FROM THE CRITICS

Booknews

This reference provides a guide for applications specialists to the most important instruments and the major recent advances in the field of applied optimization. Pardalos (industrial and systems engineering, U. of Florida) and Resende (research scientist, AT&T Laboratories) present 26 chapters in which expert contributors discuss algorithms (linear, semidefinite, quadratic, nonlinear, stochastic, and integer programming), combinatorial optimization, deterministic global optimization, decomposition methods for mathematical programming, network and hierarchical optimization, artificial neural networks and parallel algorithms in optimization, complementary and related problems, data envelopment analysis, and randomization in discrete optimization. They also cover applications (problem types, application areas) and software. Annotation c. Book News, Inc., Portland, OR (booknews.com)

     



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