English, Article edition: A PERCENTILE SEARCH HEURISTIC FOR GENERALIZED ASSIGNMENT PROBLEMS WITH A VERY LARGE NUMBER OF JOBS A. J. HIGGINS

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Physical Description
  • article
Language
  • English

Edition details

Title
  • A PERCENTILE SEARCH HEURISTIC FOR GENERALIZED ASSIGNMENT PROBLEMS WITH A VERY LARGE NUMBER OF JOBS
Author
  • A. J. HIGGINS
Physical Description
  • article
Notes
  • 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.
  • Heuristics, generalized assignment, randomized search
  • RePEc:wsi:apjorx:v:22:y:2005:i:02:p:171-188
Language
  • English
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