Distance-dependent parameter adaption for multi-objective evolutionary algorithm based on decomposition
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DOI: 10.1007/s00500-017-2980-1
Abstract: Multi-objective evolutionary algorithm based on decomposition (MOEA/D) has been proved competitive in tackling complex multi-objective optimization problems. However, the performance of MOEA/D is very sensitive to its parameter settings. Differential evolutionary (DE) operator is the… read more here.
Keywords: evolutionary algorithm; moea; objective evolutionary; distance ... See more keywords
MOEA/D with chain-based random local search for sparse optimization
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DOI: 10.1007/s00500-018-3460-y
Abstract: The goal in sparse approximation is to find a sparse representation of a system. This can be done by minimizing a data-fitting term and a sparsity term at the same time. This sparse term imposes… read more here.
Keywords: moea; chain based; sparse; sparse optimization ... See more keywords
External archive matching strategy for MOEA/D
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DOI: 10.1007/s00500-018-3499-9
Abstract: Multiobjective evolutionary algorithms based on decomposition (MOEA/D) decompose a multiobjective optimization problem (MOP) into a group of subproblems and optimizes them at the same time. The reproduction method in MOEA/D, which generates offspring solutions, has… read more here.
Keywords: matching strategy; moea; reproduction; external archive ... See more keywords
An improved epsilon constraint-handling method in MOEA/D for CMOPs with large infeasible regions
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DOI: 10.1007/s00500-019-03794-x
Abstract: This paper proposes an improved epsilon constraint-handling mechanism and combines it with a decomposition-based multi-objective evolutionary algorithm (MOEA/D) to solve constrained multi-objective optimization problems (CMOPs). The proposed constrained multi-objective evolutionary algorithm (CMOEA) is named MOEA/D-IEpsilon.… read more here.
Keywords: infeasible regions; moea; moea iepsilon; large infeasible ... See more keywords
MOEA/HD: A Multiobjective Evolutionary Algorithm Based on Hierarchical Decomposition
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DOI: 10.1109/tcyb.2017.2779450
Abstract: Recently, numerous multiobjective evolutionary algorithms (MOEAs) have been proposed to solve the multiobjective optimization problems (MOPs). One of the most widely studied MOEAs is that based on decomposition (MOEA/D), which decomposes an MOP into a… read more here.
Keywords: decomposition; multiobjective evolutionary; based hierarchical; hierarchical decomposition ... See more keywords
An MOEA/D-ACO with PBI for Many-Objective Optimization
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DOI: 10.1155/2018/5414869
Abstract: Evolutionary algorithms (EAs) are an important instrument for solving the multiobjective optimization problems (MOPs). It has been observed that the combined ant colony (MOEA/D-ACO) based on decomposition is very promising for MOPs. However, as the… read more here.
Keywords: moea; many objective; objective optimization; aco pbi ... See more keywords
A Survey on Search Strategy of Evolutionary Multi-Objective Optimization Algorithms
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DOI: 10.3390/app13074643
Abstract: The multi-objective optimization problem is difficult to solve with conventional optimization methods and algorithms because there are conflicts among several optimization objectives and functions. Through the efforts of researchers and experts from different fields for… read more here.
Keywords: moea; algorithms; multi objective; objective optimization ... See more keywords