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High Performance Multi-Objective Voyage Planning Using Local Gradient-Free Methods

A number of parallel gradient-free local optimization methods are investigated in application to problems of voyage planning for maritime ships. Two optimization algorithms are investigated, a parallel version of the Nelder-Mead Simplex method and the Subplex method with Nelder-Mead Simplex as its inner solver. Additionally, two new formulations of the optimization problem are suggested which together with an improved implementation of the objective function increases the overall performance of the model. Numerical results show the efficiency of these methods in comparison with the earlier introduced Grid search method and solvers from an open-source optimization library.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-305582
Date January 2016
CreatorsFejes, Niklas
PublisherUppsala universitet, Avdelningen för beräkningsvetenskap
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess
RelationUPTEC F, 1401-5757 ; 16061

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