Genetic algorithms for the job-shop scheduling problem with unrelated parallel constraints: Heuristic mixing method machines and precedence

In this paper, we are interested in job-shop scheduling problems with several unrelated parallel machines and precedence constraints between the operations of the jobs (with either linear or non-linear process routings). The objective is to minimize the maximum completion time (Cmax). We propose an original resolution method based on genetic algorithms and that we call , where crossovers merge the specific heuristics designed for the considered problem. After a description of both the problem and the resolution method, we present the experimental results.