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[full paper] |
Fan Wang, Andrew Lim, Hong Chen
This paper proposed a state-of-the-art local search for solving Flexible Demand Assignment problem (FDA) which considers the balance between revenue and cost in demand assignment. The hardness of finding a general accurate approximation method for solving FDA is first proved. Different than the published studies, our research splits the FDA problem into three core subproblems as operators for neighborhood construction. The three specified subproblems One Bin Repack, Two Bins Repack and Unpack are proposed completely based on mathematical modelling, computational complexity, executive conditions and greedy solving methods. Benchmark experimental results have shown that the proposed local search improved to the best published heuristics by 2.34%
Keywords: Meta-Heuristics for AI, Planning, Search, Scheduling
Citation: Fan Wang, Andrew Lim, Hong Chen: Flexible Demand Assignment Problem. In R.López de Mántaras and L.Saitta (eds.): ECAI2004, Proceedings of the 16th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2004, pp.697-701.