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Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: Dynastic Potential Crossover Operator
Author(s): Chicano, Francisco
Ochoa, Gabriela
Whitley, L Darrell
Tinós, Renato
Keywords: Recombination operator
dynastic potential
gray box optimization
Issue Date: 13-Dec-2021
Date Deposited: 16-Dec-2021
Citation: Chicano F, Ochoa G, Whitley LD & Tinós R (2021) Dynastic Potential Crossover Operator. Evolutionary Computation.
Abstract: An optimal recombination operator for two parent solutions provides the best solution among those that take the value for each variable from one of the parents (gene transmission property). If the solutions are bit strings, the offspring of an optimal recombination operator is optimal in the smallest hyperplane containing the two parent solutions. Exploring this hyperplane is computationally costly, in general, requiring exponential time in the worst case. However, when the variable interaction graph of the objective function is sparse, exploration can be done in polynomial time. In this paper, we present a recombination operator, called Dynastic Potential Crossover (DPX), that runs in polynomial time and behaves like an optimal recombination operator for low-epistasis combinatorial problems. We compare this operator, both theoretically and experimentally, with traditional crossover operators, like uniform crossover and network crossover, and with two recently defined efficient recombination operators: partition crossover and articulation points partition crossover. The empirical comparison uses NKQ Landscapes and MAX-SAT instances. DPX outperforms the other crossover operators in terms of quality of the offspring and provides better results included in a trajectory and a population-based metaheuristic, but it requires more time and memory to compute the offspring.
DOI Link: 10.1162/evco_a_00305
Rights: This is the author's final version accepted for publication in Evolutionary Computation published by MIT Press:
Notes: Output Status: Forthcoming/Available Online
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