Cooperative Strategies for Solving the Bicriteria Sparse Multiple Knapsack Problem

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...

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Bibliographic Details
Published in:Journal of heuristics 2002-03, Vol.8 (2), p.215
Main Authors: Salman, F Sibel, Kalagnanam, Jayant R, Murthy, Sesh, Davenport, Andrew
Format: Article
Language:English
Subjects:
Algorithms
Cooperation
Graph representations
Heuristic
Integer programming
Knapsack problem
Optimization algorithms
Packing problem
Problem solving
Sparsity
Studies
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Summary: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. [PUBLICATION ABSTRACT]
ISSN:1381-1231
1572-9397
DOI:10.1023/A:1017964608086