An Orthogonal Genetic Algorithm for Job Shop Scheduling Problems with Multiple Objectives

The job shop scheduling problem with multiple objectives is a research hotspot. In this paper, a multi-objective orthogonal genetic algorithm(MOOGA) was proposed to solve this problem. MOOGA integrated the orthogonal design method into the crossover operator, which could generate both outstanding and evenly distributed filial individuals, and improve the efficiency of the algorithm. A fitness calculating method was designed to help MOOGA move towards the Pareto front. Numerical results verify effectiveness and efficiency of the algorithm.