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Stochastic Optimization - Seeing the Optimal for the Uncertain

Editor

Listed:
  • Ioannis Dritsas

Abstract

Stochastic Optimization Algorithms have become essential tools in solving a wide range of difficult and critical optimization problems. Such methods are able to find the optimum solution of a problem with uncertain elements or to algorithmically incorporate uncertainty to solve a deterministic problem. They even succeed in fighting uncertainty with uncertainty. This book discusses theoretical aspects of many such algorithms and covers their application in various scientific fields.

Individual chapters are listed in the "Chapters" tab

Suggested Citation

  • Ioannis Dritsas (ed.), 2011. "Stochastic Optimization - Seeing the Optimal for the Uncertain," Books, IntechOpen, number 900, January-J.
  • Handle: RePEc:ito:pbooks:900
    DOI: 10.5772/623
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    File URL: https://www.intechopen.com/books/900
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    Book Chapters

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    More about this item

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

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