Article ID: | iaor20023464 |
Country: | Netherlands |
Volume: | 8 |
Issue: | 2 |
Start Page Number: | 215 |
End Page Number: | 239 |
Publication Date: | Mar 2002 |
Journal: | Journal of Heuristics |
Authors: | Murthy Sesh, Kalagnanam Jayant R., Salman F. Sibel, Davenport Andrew |
Keywords: | heuristics |
For hard optimization problems, it is difficult to design heuristic algorithms which exhibit uniformly superior performance for all problem instances. As a result it becomes necessary to tailor the algorithms based on the problem instance. In this paper, we introduce the use of a cooperative problem solving team of heuristics that evolves algorithms for a given problem instance. The efficacy of this method is examined by solving six difficult instances of a bicriteria sparse multiple knapsack problem. Results indicate that such tailored algorithms uniformly improve solutions as compared to using predesigned heuristic algorithms.