Article ID: | iaor19981164 |
Country: | Netherlands |
Volume: | 83 |
Issue: | 2 |
Start Page Number: | 347 |
End Page Number: | 364 |
Publication Date: | Jun 1995 |
Journal: | European Journal of Operational Research |
Authors: | Loureno Helena Ramalhinho |
We present a computational study of different local search and large-step optimization methods to solve the job-shop scheduling problem. We review local optimization methods and propose a two-phase optimization method, known as large-step optimization, which has recently been introduced for the traveling salesman problem. The first phase of this new method consists of a large optimized transition in the current solution, while the second phase is basically a local search method. We present extensive computational results obtained from various combinations of local search and large-step optimization techniques. From the computational results we can conclude that the large-step optimization methods outperform the simulated annealing method and find more frequently an optimal schedule than the other studied methods.