| Article ID: | iaor1998703 |
| Country: | Netherlands |
| Volume: | 77 |
| Issue: | 2 |
| Start Page Number: | 208 |
| End Page Number: | 223 |
| Publication Date: | Sep 1994 |
| Journal: | European Journal of Operational Research |
| Authors: | Chang Pei Chann, Jiang Yen Shean |
| Keywords: | artificial intelligence: expert systems |
This paper presents a state-space search approach for parallel processor scheduling problems with arbitrary precedence relations. The tasks to be scheduled are non-preemptive and have different dependence structures. The objective is to minimize the makespan and this problem has been identified as an NP-complete problem. As a result, the optimal solution to this problem is intractable and heuristic approaches are justified. In our approach, we will adopt the following strategies: (1) a state-space representation scheme is applied for the problem formulation, (2) A* and Best-First search techniques are presented and the possible variations of these two approaches are discussed, and (3) different bounding strategies and heuristics for A* and Best-First searches are explored. Efficiency and solution quality of each bound and heuristic are evaluated by experimental examples. To solve the problem in practical sizes, the EST/CP heuristic is developed and experimental results show that the heuristic is very encouraging and outperforms conventional methods. In summary, the state-space search approach provides a promising paradigm for parallel processor scheduling problems.