Ant colony systems for the single-machine total weighted earliness tardiness scheduling problem

• Published in: Journal of scheduling Vol. 19; no. 2; pp. 191 - 205
• Main Authors: M’Hallah, Rym, Alhajraf, Ali
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.04.2016; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Benchmarking; Business and Management; Calculus of Variations and Optimal Control; Optimization; Colonies; Deviation; Employment; Heuristic; Job shops; Just in time; Manufacturing; Mathematical models; Mathematical programming; Operations Research/Decision Theory; Optimization; Production scheduling; Scheduling; Searching; Service industries; Simulation; Studies; Supply Chain Management; Utilities; Ant colony systems; Variable neighborhood search; Weighted earliness tardiness; Single machine; Simulated annealing
• ISSN: 1094-6136; 1099-1425
• DOI: 10.1007/s10951-015-0429-x

Single-machine weighted earliness tardiness scheduling is a prevalent problem in just-in-time production environments. Yet, the case with distinct due dates is strongly NP-hard. Herein, it is approximately solved using ASV, an ant colony-based system with a reduced number of ants and of colonies and with daemon actions that explore the search space around the ants using a variable neighborhood search (VNS). The numerical investigation provides computational proof of the utility of the daemon actions. In addition, it infers that these latter can be applied either to the initial or to subsequent colonies. Furthermore, it highlights the importance of using ant colony optimization as the multiple restart engine of VNS. Finally, it shows that ASV obtains the optimum for most small-sized instances. It has a 0.2 % average deviation from the optimum over all benchmark instances.