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Scalarizing functions in solving multi-objective problem-an evolutionary approach
Author(s) -
D. Vasumathi,
S. Thangavelu
Publication year - 2019
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v13.i3.pp974-981
Subject(s) - evolutionary algorithm , mathematical optimization , function (biology) , computer science , mathematics , biology , evolutionary biology
Scalarizing functions had long been observed for optimization of multi-objective problems. Scalarizing functions on multi-objective problem along with Differential Evolution (DE) algorithm variants had been used to analyze the effect of scalarizing functions. The main purpose is to find the better scalarizing function which can be applied for optimization. The effective solution of the multi-objective problem depends on the various factors like the DE algorithm and the scalarizing functions used. Multi objective evolutionary algorithm (MOEA) framework in java had been used for performing the analysis. The Obtained results showed that Tchebysheff scalarization function performs better than the other scalarizing functions on various indicator functions used.

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