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Local Optima and Weight Distribution in the Number Partitioning Problem

Khulood Alyahya and Jonathan E. Rowe

School of Computer Science, University of Birmingham, B15 2TT, UK
kya020@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.

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