A genetic algorithm for an industrial multiprocessor flow shop scheduling problem with recirculation

We propose in this paper an effective heuristic algorithm to solve a scheduling problem that comes from industry. The workshop is an hybrid flow shop with recirculation and the problem is to perform jobs between a release date and a due date, in order to minimize the weighted number of tardy jobs. Firstly, an integer linear programming formulation of the problem is proposed, then a lower bound, a greedy algorithm and a genetic algorithm are described as approximate methods. To evaluate these heuristics, experiences on instances like industrial ones are computed, and show the efficiency of the genetic algorithm. (C) 2003 Elsevier B.V. All rights reserved.