Hybrid metaheuristics in combinatorial optimization: A survey

Abstract

Research in metaheuristics for combinatorial optimization problems has lately experienced a noteworthy shift towards the hybridization of metaheuristics with other techniques for optimization. At the same time, the focus of research has changed from being rather algorithm-oriented to being more problem-oriented.\ud Nowadays the focus is on solving the problem at hand in the best way possible, rather than\ud promoting a certain metaheuristic. This has led to an enormously fruitful cross-fertilization of different areas of optimization. This cross-fertilization is documented by a multitude of powerful hybrid algorithms that were obtained by combining components from several different optimization techniques. Hereby, hybridization is not restricted to the combination of different metaheuristics but includes, for example, the combination of exact algorithms and metaheuristics. In this work we provide a survey of some of the most important lines of hybridization. The literature review is accompanied by the presentation of illustrative examples.Peer ReviewedPostprint (published version

Metaheuristics for agricultural land use optimization. A review

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“…The specific characteristics of the latter, e.g., the number of objectives and constraints could also guide this choice. Many literature reviews describing the historical development of metaheuristics and their basic concepts have been published (Bahesti and Shamsuddin 2013;Blum et al 2011;Boussaïd et al 2013;Jarraya and Bouri 2012;Jones et al 2002;Madhuri and Deep 2009). We refer interested readers to the recent review of metaheuristics (Boussaïd et al 2013).…”

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