The study of comparisons of three crossover operators in genetic algorithm for solving single machine scheduling problem

Abstract

genetic algorithm is a common method for solving combinatorial optimization problems and the selection of crossover operators in genetic algorithm will directly affect the performance of the algorithm. In this paper, we compare the performance of three crossover operators, partially mapped crossover operator (PMX), order based crossover operator (OBX), and adaptation of the edge recombination crossover operator (aERX), under same genetic algorithm framework in solving the un-weighted single machine scheduling problem with sequence dependent setup times. It is concluded that the performance of PMX crossover operator is better than the other two crossover operators from the computational results.