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. Nowadays the focus is on solving the problem at hand in the best way possible, rather than 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.

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Hybrid metaheuristics in combinatorial optimization: A survey

A survey for the quadratic assignment problem

Facility layout problems: a survey

Facility layout problem (FLP) is defined as the placement of facilities in a plant area, with the aim of determining the most effective arrangement in accordance with some criteria or objectives under certain constraints, such as shape, size, orientation, and pick-up/drop-off point of the facilities. It has been over six decades since Koopmans and Beckmann published their seminal paper on modeling the FLP. Since then, there have been improvements to these researchers’ original quadratic assignment problem. However, research on many aspects of the FLP is still in its initial stage; hence, the issue is an interesting field to work on. Here, a review of literature is made by referring to numerous papers about FLPs. The study is mainly motivated by the current and prospective trends of research on such points as layout evolution, workshop characteristics, problem formulation, and solution methodologies. It points to gaps in the literature and suggests promising directions for future research on FLP.

Classification of facility layout problems: a review study

https://researchrepository.wvu.edu/cgi/viewcontent.cgi?article=2202&context=etd

Simulated annealing heuristics for the dynamic facility layout problem

A Hybrid Genetic Algorithm for the Dynamic Plant Layout Problem

A hybrid genetic algorithm for dynamic layout

The dynamic plant layout problem (DPLP) deals with multi-period layout plans. Genetic algorithms have proved to be effective in solving DPLPs. In this research we consider a constraint on rearrangement. Such constraints may have to be considered not only in multi-period plant layout, but also in multi-period plant location and multi-period cellular manufacturing. We suggest proactive and reactive heuristic methods that can be used to modify existing genetic algorithms for the constrained situation. An extensive computational study is carried out to compare the proposed heuristics.

Modelling rearrangement constraints in dynamic layout

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A Hybrid Genetic Algorithm for the Dynamic Plant Layout Problem

A hybrid genetic algorithm for dynamic layout

Modelling rearrangement constraints in dynamic layout