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Harmony Search with Differential Mutation Based Pitch Adjustment

A. Kai Qin 1 Florence Forbes 1 
1 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology
Abstract : Harmony search (HS), as an emerging metaheuristic technique mimicking the improvisation behavior of musicians, has demonstrated strong efficacy in solving various numerical and real-world optimization problems. This work presents a harmony search with differential mutation based pitch adjustment (HSDM) algorithm, which improves the original pitch adjustment operator of HS using the self-referential differential mutation scheme that features differential evolution - another celebrated metaheuristic algorithm. In HSDM, the differential mutation based pitch adjustment can dynamically adapt the properties of the landscapes being explored at different searching stages. Meanwhile, the pitch adjustment operator's execution probability is allowed to vary randomly between 0 and 1, which can maintain both wild and fine exploitation throughout the searching course. HSDM has been evaluated and compared to the original HS and two recent HS variants using 16 numerical test problems of various searching landscape complexities at 10 and 30 dimensions. HSDM almost always demonstrates superiority on all test problems.
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Submitted on : Thursday, January 24, 2013 - 11:03:53 AM
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A. Kai Qin, Florence Forbes. Harmony Search with Differential Mutation Based Pitch Adjustment. GECCO'11 - 13th annual conference on Genetic and evolutionary computation, Jul 2011, Dublin, Ireland. pp.545-552, ⟨10.1145/2001576.2001651⟩. ⟨hal-00780523⟩



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