Experimental evaluation of an evolutionary scheduling scheme for the job shop scheduling problem

Scheduling in a constrained environment is a complex and difficult process. Genetic algorithm (GA) approach has been increasingly used to solve various combinatorial optimization type problems. In this paper, we carry out experiments to investigate a GA based approach to the job shop scheduling problem (JSSP). We propose genetic heuristics to be used in our GA. We evaluate the performance of the proposed approach using well known benchmark instances for the JSSP.