Article ID: | iaor20072862 |
Country: | Netherlands |
Volume: | 13 |
Issue: | 2 |
Start Page Number: | 151 |
End Page Number: | 165 |
Publication Date: | Apr 2007 |
Journal: | Journal of Heuristics |
Authors: | Chou Shuo-Yan, Lin Shih-Wei, Chen Shih-Chieh |
Keywords: | heuristics: local search |
This study addresses a class of single-machine scheduling problems involving a common due date where the objective is to minimize the total job earliness and tardiness penalties. A genetic algorithm (GA) approach and a simulated annealing (SA) approach utilizing a greedy local search and three well-known properties in the area of common due date scheduling are developed. The developed algorithms enable the starting time of the first job not at zero and were tested using a set of benchmark problems. From the viewpoints of solution quality and computational expenses, the proposed approaches are efficient and effective for problems involving different numbers of jobs, as well as different processing time, and earliness and tardiness penalties.