par Blum, Christian 
;Sampels, Michaël
Référence Journal of mathematical modelling and algorithms, 3, 3, page (285-308)
Publication Publié, 2004
;Sampels, Michaël Référence Journal of mathematical modelling and algorithms, 3, 3, page (285-308)
Publication Publié, 2004
Article révisé par les pairs
| Résumé : | We deal with the application of ant colony optimization to group shop scheduling, which is a general shop scheduling problem that includes, among others, the open shop scheduling problem and the job shop scheduling problem as special cases. The contributions of this paper are twofold. First, we propose a neighborhood structure for this problem by extending the well-known neigh-borhood structure derived by Nowicki and Smutnicki for the job shop scheduling problem. Then, we develop an ant colony optimization approach, which uses a strong non-delay guidance for constructing solutions and which employs black-box local search procedures to improve the constructed solutions. We compare this algorithm to an adaptation of the tabu search by Nowicki and Smutnicki to group shop scheduling. Despite its general nature, our algorithm works particularly well when applied to open shop scheduling instances, where it improves the best known solutions for 15 of the 28 tested instances. Moreover, our algorithm is the first competitive ant colony optimization approach for job shop scheduling instances. © 2004 Kluwer Academic Publishers. |
