Evolution programs for job-shop scheduling

This paper explains how to minimize a makespan of the job shop scheduling problem using evolutionary programs. So the job shop scheduling problem is among the hardest combinatorial problems. Not only is it NP complete but it is one of the worst NP complete class members, but for better performance it is very important to develop an efficient representational scheme and effective genetic operators. Our objective is to improve performance of the evolutionary programs based approach to job-shop scheduling problems by creating a new representation of the chromosome where we integrate the precedence constraint, and the new genetic operators associated with this original representation.