Coevolutionary genetic algorithm for job shop scheduling problems

Abstract

In this paper a coevolutionary genetic algorithm (CEGA) has been proposed for solving the job-shop scheduling problem (JSSP). Here the JSSP is divided into a number of subproblems, and the CEGA encourages the parallel evolution of partial solutions. This approach combines and extends previous evolutionary computation techniques used to solve similar optimization problems. Initial computational results indicate the CEGA performs favourably when compared to other approaches and that a number of high quality solutions to the problem are produced on each run.