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Local Optima and Weight Distribution in the Number Partitioning ProblemKhulood Alyahya and Jonathan E. Rowe School of Computer Science, University of Birmingham, B15 2TT, UKkya020@cs.bham.ac.uk J.E.Rowe@cs.bham.ac.uk http://www.cs.bham.ac.uk Abstract. This paper investigates the relation between the distribution of the weights and the number of local optima in the Number Partitioning Problem (NPP). The number of local optima in the 1-bit flip landscape was found to be strongly and negatively correlated with the coefficient of variation (CV) of the weights. The average local search cost using the 1-bit flip operator was also found to be strongly and negatively correlated with the CV of the weights. A formula based on the CV of the weights for estimating the average number of local optima in the 1-bit flip landscape is proposed in the paper. The paper also shows that the CV of the weights has a potentially useful application in guiding the choice of heuristic search algorithm. Keywords: Combinatorial optimisation, phase transition, partitioning problem, makespan scheduling, fitness landscape LNCS 8672, p. 862 ff. lncs@springer.com
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