PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A Memetic Algorithm for the Multidimensional Assignment Problem
Gregory Gutin and Daniel Karapetyan
In: Stochastic Local Search Workshop 2009(2009).

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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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:6578
Deposited By:Gregory Gutin
Deposited On:08 March 2010