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Old and New Non-Gradient Methods in Engineering Optimization

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Emerging Methods for Multidisciplinary Optimization

Part of the book series: International Centre for Mechanical Sciences ((CISM,volume 425))

Abstract

Current interest in non-gradient optimization can be attributed to two, distinct developments. The first stems from studying natural processes and the second from fast progress in the computing environment. The first has resulted in new optimization techniques like simulated annealing, tabu search and genetic algorithms whilst the second has made many of the existing zero order methods computationally affordable. This chapter discusses simulated annealing, tabu search, dynamic programming, random methods and other heuristics. A variety of illustrative examples is provided together with practical examples drawn from structural mechanics.

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  1. Mechanical Engineering, The University of Liverpool, Liverpool, UK

    J. Blachut

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  1. The University of Liverpool, UK

    Jan Blachut

  2. University of Siegen, Germany

    Hans A. Eschenauer

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Blachut, J. (2001). Old and New Non-Gradient Methods in Engineering Optimization. In: Blachut, J., Eschenauer, H.A. (eds) Emerging Methods for Multidisciplinary Optimization. International Centre for Mechanical Sciences, vol 425. Springer, Vienna. https://doi.org/10.1007/978-3-7091-2756-8_2

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  • DOI: https://doi.org/10.1007/978-3-7091-2756-8_2

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-83335-3

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