Memetic algorithms and hyperheuristics applied to a multiobjectivised two-dimensional packing problem

Eduardo Segredo (), Carlos Segura () and Coromoto León ()

Journal of Global Optimization, 2014, vol. 58, issue 4, 769-794

Abstract: Packing problems are np-hard problems with several practical applications. A variant of a 2d Packing Problem (2 dpp) was proposed in the gecco 2008 competition session. In this paper, Memetic Algorithms ( mas) and Hyperheuristics are applied to a multiobjectivised version of the 2 dpp. Multiobjectivisation is the reformulation of a mono-objective problem into a multi-objective one. The main aim of multiobjectivising the 2 dpp is to avoid stagnation in local optima. First generation mas refers to hybrid algorithms that combine a population-based global search with an individual learning process. A novel first generation ma is proposed, and an original multiobjectivisation method is applied to the 2 dpp. In addition, with the aim of facilitating the application of such first generation mas from the point of view of the parameter setting, and of enabling their usage in parallel environments, a parallel hyperheuristic is also applied. Particularly, the method applied here is a hybrid approach which combines a parallel island-based model and a hyperheuristic. The main objective of this work is twofold. Firstly, to analyse the advantages and drawbacks of a set of first generation mas. Secondly, to attempt to avoid those drawbacks by applying a parallel hyperheuristic. Moreover, robustness and scalability analyses of the parallel scheme are included. Finally, we should note that our methods improve on the current best-known solutions for the tested instances of the 2 dpp. Copyright Springer Science+Business Media New York 2014

Keywords: Memetic algorithms; Hyperheuristics; Multiobjectivisation; Packing problems; Parameter setting (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10898-013-0088-4

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