Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/464
Title: Continuous variable neighbourhood search with modified Nelder-Mead for non-differentiable optimization
Authors: Dražić, Milan 
Dražić, Zorica 
Mladenović, Nenad
Urošević, Dragan
Zhao, Qiu Hong
Affiliations: Numerical Mathematics and Optimization 
Numerical Mathematics and Optimization 
Keywords: global optimization;heuristics;non-differentiable optimization;simplex method;variable neighbourhood search.
Issue Date: 1-Jan-2016
Journal: IMA Journal of Management Mathematics
Abstract: 
Several variants of variable neighbourhood search (VNS) for solving unconstrained and constrained continuous optimization problems have been proposed in the literature. In this paper, we suggest two new variants, one of which uses the recent modified Nelder-Mead (MNM) direct search method as a local search and the other an extension of the MNM method obtained by increasing the size of the simplex each time the search cannot be continued. For these new and some previous VNS variants, extensive computational experiments are performed on standard and large non-differentiable test instances. Some interesting observations regarding comparison of some VNS variants with NM based local search are made.
URI: https://research.matf.bg.ac.rs/handle/123456789/464
ISSN: 1471678X
DOI: 10.1093/imaman/dpu012
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