Push-n-Pop Genes Xchange (PPX)—A New Crossover Operator in Genetic Algorithm

Abstract

Crossover operator plays a crucial role in of Genetic Algorithm (GA). It is one of the key elements in GA which is responsible for producing offsprings usually called “solutions” by way of recombining information from two parents providing experimental mechanism of the algorithm. Crossover operator is a critical factor that affects performance of GA due to its impact on time being used in the crossover process. This paper introduces a new crossover operator named Push-n-Pop Genes Xchange Operator (PPX). Evaluation of its performance in terms of processing time is also presented in this paper. The results of PPX’s performance with all other six existing GA’s crossover operators ( Half-uniform, Surrogate, Segmented, Shuffle, Two-point, and Uniform ) show that PPX is in comparable using different population sizes 30, 50, and 100. Results also show that the new crossover operator performed better with a maximum improvement of 13.1% when population size was gradually increased from 30 to 100.

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