Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
474097 | Computers & Operations Research | 2008 | 15 Pages |
The problem of scheduling multiple jobs on a single machine so that they are completed by a common specified date is addressed in this paper. This type of scheduling set costs depend on whether a job is finished before (earliness) or after (tardiness) the specified due date. The objective is to minimize a summation of earliness and tardiness penalty costs. Minimizing these costs pushes the completion time of each job as close as possible to the due date. The use of differential evolution as the optimization heuristic to solve this problem is investigated in this paper. Computational experiments over multiple (280 in total) public benchmark problems with up to 1000 jobs to be scheduled show the effectiveness of the proposed approach. The results obtained are of high quality putting new upper bounds to 60% of the benchmark instances.