Engineering Optimization and Industrial Applications

Xin-She Yang ()
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Xin-She Yang: Middlesex University, School of Science and Technology

A chapter in Surrogate-Based Modeling and Optimization, 2013, pp 393-412 from Springer

Abstract: Abstract Design optimization is important in engineering and industrial applications. It is usually very challenging to find optimum designs, which require both efficient optimization algorithms and high-quality simulators that are often time-consuming. To some extent, an optimization process is equivalent to a self-organizing system, and the organized states are the optima that are to be searched for. In this chapter, we discuss both optimization and self-organization in a unified framework, and we use three metaheuristic algorithms, the firefly algorithm, the bat algorithm and cuckoo search, as examples to see how this self-organized process works. We then present a set of nine design problems in engineering and industry. We also discuss the challenging issues that need to be addressed in the near future.

Keywords: Bat algorithm; Cuckoo search; Firefly algorithm; Optimization; Metaheuristic; Self-organizaion (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4614-7551-4_16

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DOI: 10.1007/978-1-4614-7551-4_16

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