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Heuristic Algorithm with Oscillation Strategy for a New Class of Assignment Problem

✍ Scribed by Jia-xiang LUO; Li-xin TANG; Yue-ming HU


Publisher
Elsevier
Year
2009
Weight
244 KB
Volume
29
Category
Article
ISSN
1874-8651

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✦ Synopsis


A new class of assignment problem which roots in the optimization management of slabs in steel industry is considered in this article. Compared with the generalized assignment problem, flow constraints should be considered in this problem besides the capacity constraints when assigning items to knapsacks. This problem could be reduced to the generalized assignment problem, and so is NP-hard. A heuristic with oscillation strategy and long-term memory list is proposed to solve it. The oscillation strategy makes it possible that the local search oscillates between the feasible and infeasible solution spaces to find better feasible solutions. A long-term memory list is embedded to encourage the diverse moves of items, which improves the diversity of the algorithm. In order to testify the efficiency of the heuristic, 23 instances have been randomly generated for the computational experiments. The results show that for small-size instances, the maximum deviation of the heuristic from the optimal solution is 0.55% and for larger-size instances, the heuristic could find good solutions in a very short time.


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✍ Igor Litvinchev; Miguel Mata; Socorro Rangel; Jania Saucedo πŸ“‚ Article πŸ“… 2010 πŸ› Elsevier Science 🌐 English βš– 314 KB

A Lagrangian based heuristic is proposed for many-to-many assignment problems taking into account capacity limits for task and agents. A modified Lagrangian bound studied earlier by the authors is presented and a greedy heuristic is then applied to get a feasible Lagrangian-based solution. The latte