Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/29468
Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings
Author(s): Chicano, Francisco
Ochoa, Gabriela
Whitley, Darrell
Tinós, Renato
Title: Quasi-Optimal Recombination Operator
Editor(s): Liefooghe, A
Paquete, L
Citation: Chicano F, Ochoa G, Whitley D & Tinós R (2019) Quasi-Optimal Recombination Operator. In: Liefooghe A & Paquete L (eds.) Evolutionary Computation in Combinatorial Optimization. Lecture Notes in Computer Science, 11452. EvoCOP 2019: European Conference on Evolutionary Computation in Combinatorial Optimization, Leipzig, Germany, 24.04.2019-26.04.2019. Cham, Switzerland: Springer International Publishing, pp. 131-146. https://doi.org/10.1007/978-3-030-16711-0_9
Issue Date: 2019
Series/Report no.: Lecture Notes in Computer Science, 11452
Conference Name: EvoCOP 2019: European Conference on Evolutionary Computation in Combinatorial Optimization
Conference Dates: 2019-04-24 - 2019-04-26
Conference Location: Leipzig, Germany
Abstract: The output of an optimal recombination operator for two parent solutions is a solution with the best possible value for the objective function among all the solutions fulfilling the gene transmission property: the value of any variable in the offspring must be inherited from one of the parents. This set of solutions coincides with the largest dynastic potential for the two parent solutions of any recombination operator with the gene transmission property. In general, exploring the full dynastic potential is computationally costly, but if the variables of the objective function have a low number of non-linear interactions among them, the exploration can be done in O(4β(n+m)+n2) time, for problems with n variables, m subfunctions and β a constant. In this paper, we propose a quasi-optimal recombination operator, called Dynastic Potential Crossover (DPX), that runs in O(4β(n+m)+n2) time in any case and is able to explore the full dynastic potential for low-epistasis combinatorial problems. We compare this operator, both theoretically and experimentally, with two recently defined efficient recombination operators: Partition Crossover (PX) and Articulation Points Partition Crossover (APX). The empirical comparison uses NKQ Landscapes and MAX-SAT instances.
Status: AM - Accepted Manuscript
Rights: This is a post-peer-review, pre-copyedit version of an article published in Liefooghe A & Paquete L (eds.) Evolutionary Computation in Combinatorial Optimization. Lecture Notes in Computer Science, 11452. EvoCOP 2019: European Conference on Evolutionary Computation in Combinatorial Optimization, Leipzig, Germany, 24.04.2019-26.04.2019. Cham, Switzerland: Springer International Publishing, pp. 131-146. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-16711-0_9

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