Comparing Genetic Algorithm and Variable Neighborhood Search Method for Solving Job Shop Problem

Abstract

Job Shop scheduling problem is one of the most complex and researched problems in the field of production planning. In this paper, two methods for solving Job Shop scheduling problem are presented and com­pared. The genetic algorithm and variable neighborhood search method were chosen and implemented in software for solving Job Shop problem. The paper first briefly presents Job Shop scheduling problem and then ex­plains the development of solving software and implementation of selected solution methods. The results of using implemented genetic algorithm and variable neighborhood search method are presented on test instances with various dimensions. Solutions obtained using these two methods were put in comparison and analyzed, as well as compared with the optimal or best-known solutions in the literature.