Abstract
In this article, we will examine whether the Problem Aware Local Search, an efficient method initially proposed for the DNA Fragment Assembly Problem, can also be used in other application domains and with other optimization problems. The main idea is to maintain the key features of PALS and apply it to different permutation-based combinatorial problems. In order to carry out a comprehensive analysis, we use a wide benchmark of well-known problems with different kinds of variation operators and fitness functions, such as the Quadratic Assignment Problem, the Flow Shop Scheduling Problem, and the Multiple Knapsack Problem. We also discuss the main design alternatives for building an efficient and accurate version of PALS for these problems in a competitive manner. In general, the results show that PALS can achieve high-quality solutions for these problems and do it efficiently.
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Acknowledgements
The first author is supported by the Universidad Nacional de La Pampa, and the ANPCYT under contract PICTO 2011-0278 and the Incentive Program. The second and third authors have been partially funded by Project Number 8.06/5.47.4142 in collaboration with the VSB-Technical University of Ostrava and by the Spanish MINECO Project TIN2014-57341-R (http://moveon.lcc.uma.es).
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Minetti, G.F., Luque, G. & Alba, E. The Problem Aware Local Search algorithm: an efficient technique for permutation-based problems. Soft Comput 21, 5193–5206 (2017). https://doi.org/10.1007/s00500-017-2515-9
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DOI: https://doi.org/10.1007/s00500-017-2515-9