Cooperative Strategies for Solving the Bicriteria Sparse Multiple Knapsack Problem |
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Authors: | F. Sibel Salman Jayant R. Kalagnanam Sesh Murthy Andrew Davenport |
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Affiliation: | (1) GSIA, Carnegie Mellon University, Pittsburgh, PA 15213, USA;(2) IBM T. J. Watson Research Center, Yorktown Heights, NY 10598, USA |
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Abstract: | 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. |
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Keywords: | multiple knapsack bicriteria multiple heuristics cooperation asynchronous teams |
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