Abstract
The Multidimensional Assignment Problem (MAP) is a combinatorial optimization problem that arises in many important practical areas including capital investment, dynamic facility location, elementary particle path reconstruction, multiple target tracking and sensor fusion. Since the solution space of the MAP increases exponentially with the problem parameters, and the problem has exponentially many local minima, only moderate-sized instances can be solved to optimality. We investigate the combinatorial structure of the solution space by extending a concept of Hamming distance. The results of numerical experiments indicate a linear trend for average Hamming distance to optimal solution for the cases where one of the parameters is fixed.
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Kammerdiner, A.R., Krokhmal, P.A., Pardalos, P.M. (2007). Characteristics of the Distribution of Hamming Distance Values Between Multidimensional Assignment Problem Solutions. In: Pardalos, P.M., Murphey, R., Grundel, D., Hirsch, M.J. (eds) Advances in Cooperative Control and Optimization. Lecture Notes in Control and Information Sciences, vol 369. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74356-9_21
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DOI: https://doi.org/10.1007/978-3-540-74356-9_21
Publisher Name: Springer, Berlin, Heidelberg
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