A percentile search heuristic for generalized assignment problems with a very large number of jobs

A percentile search heuristic for generalized assignment problems with a very large number of jobs

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Article ID: iaor20071442
Country: Singapore
Volume: 22
Issue: 2
Start Page Number: 171
End Page Number: 188
Publication Date: Jun 2005
Journal: Asia-Pacific Journal of Operational Research
Authors:
Keywords: heuristics
Abstract:

This article presents a new heuristic for generalized assignment problems with a very large number of jobs. The heuristic applies a probabilistic acceptance of a move, based on a percentile threshold, using information from recent moves. This percentile search heuristic (PSH) is compared to tabu search, simulated annealing, and threshold accepting using a rigorous computational experimentation with randomly generated problem instances of up to 50,000 jobs and 40 agents. The PSH did find the best solution among the heuristics for 45% of the instances, particularly larger size problems, versus 30% for tabu search, but required more fine-tuning of the heuristic parameters.

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