Abstract
The Multidimensional Assignment Problem (MAP or 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 have also a number of applications. In this paper we propose a memetic algorithm for MAP that is a combination of a genetic algorithm with a local search procedure. The main contribution of the paper is an idea of dynamically adjusted generation size, that yields an outstanding flexibility of the algorithm to perform well for both small and large fixed running times.
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Gutin, G., Karapetyan, D.: A memetic algorithm for the multidimensional assignment problem. Preprint in arXiv (2009), http://arxiv.org/abs/0906.0862
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Gutin, G., Karapetyan, D. (2009). A Memetic Algorithm for the Multidimensional Assignment Problem. In: Stützle, T., Birattari, M., Hoos, H.H. (eds) Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics. SLS 2009. Lecture Notes in Computer Science, vol 5752. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03751-1_12
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DOI: https://doi.org/10.1007/978-3-642-03751-1_12
Publisher Name: Springer, Berlin, Heidelberg
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