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Evolutionary dynamic optimization : a survey of the state of the art
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Nguyen, Trung Thanh, Yang, Shengxiang and Branke, Jürgen (2012) Evolutionary dynamic optimization : a survey of the state of the art. Swarm and Evolutionary Computation, Volume 6 . pp. 1-24. doi:10.1016/j.swevo.2012.05.001
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Official URL: http://dx.doi.org/10.1016/j.swevo.2012.05.001
Abstract
Optimization in dynamic environments is a challenging but important task since many real-world optimization problems are changing over time. Evolutionary computation and swarm intelligence are good tools to address optimization problems in dynamic environments due to their inspiration from natural self-organized systems and biological evolution, which have always been subject to changing environments. Evolutionary optimization in dynamic environments, or evolutionary dynamic optimization (EDO), has attracted a lot of research effort during the last 20 years, and has become one of the most active research areas in the field of evolutionary computation. In this paper we carry out an in-depth survey of the state-of-the-art of academic research in the field of EDO and other meta-heuristics in four areas: benchmark problems/generators, performance measures, algorithmic approaches, and theoretical studies. The purpose is to for the first time (i) provide detailed explanations of how current approaches work; (ii) review the strengths and weaknesses of each approach; (iii) discuss the current assumptions and coverage of existing EDO research; and (iv) identify current gaps, challenges and opportunities in EDO.
| Item Type: | Journal Article | ||||
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| Divisions: | Faculty of Social Sciences > Warwick Business School > Operational Research & Management Sciences Faculty of Social Sciences > Warwick Business School |
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| Journal or Publication Title: | Swarm and Evolutionary Computation | ||||
| Publisher: | Elsevier BV | ||||
| ISSN: | 2210-6502 | ||||
| Official Date: | October 2012 | ||||
| Dates: |
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| Volume: | Volume 6 | ||||
| Page Range: | pp. 1-24 | ||||
| DOI: | 10.1016/j.swevo.2012.05.001 | ||||
| Status: | Peer Reviewed | ||||
| Publication Status: | Published | ||||
| Access rights to Published version: | Restricted or Subscription Access | ||||
| Funder: | Engineering and Physical Sciences Research Council (EPSRC), UK ORS Award, School of Computer Science, University of Birmingham | ||||
| Grant number: | EP/E058884/1, EP/E060722/1, EP/E060722/2 (EPSRC) |
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