Heuristics and a hybrid meta-heuristic for a generalized job-shop scheduling problem

This paper proposes to solve a generalized job-shop scheduling problem (with unrelated parallel machines and precedence constraints between the jobs operations) by using, on the one hand, several original static and dynamic heuristics relying on the machines potential load and, on the other hand, an original hybrid genetic algorithm meta-heuristic. The objective is to minimize jobs completion time. Experimental results using different types of data and the comparison of both approaches are reported.