Abstract
The Multidimensional Assignment Problem (MAP) (abbreviated s-AP in the case of s dimensions) is an extension of the well-known assignment problem. The most studied case of MAP is 3-AP, though the problems with larger values of s also have a large number of applications. We consider several known neighborhoods, generalize them and propose some new ones. The heuristics are evaluated both theoretically and experimentally and dominating algorithms are selected. We also demonstrate that a combination of two neighborhoods may yield a heuristics which is superior to both of its components.
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A preliminary version of this paper was published in Golumbic Festschrift, volume 5420 of Lect. Notes Comput. Sci., pages 100–115, Springer, 2009.
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Karapetyan, D., Gutin, G. Local search heuristics for the multidimensional assignment problem. J Heuristics 17, 201–249 (2011). https://doi.org/10.1007/s10732-010-9133-3
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DOI: https://doi.org/10.1007/s10732-010-9133-3