Adjust weight vectors in MOEA/D for bi-objective optimization problems with discontinuous Pareto fronts

Multi-objective evolutionary algorithm based on decomposition (MOEA/D) is a recently proposed algorithm which is a research focus in the field of multi-objective evolutionary optimization. It decomposes a multi-objective problem into subproblems by mathematic programming methods and applies evolutio...

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Vydané v:	Soft computing (Berlin, Germany) Ročník 22; číslo 12; s. 3997 - 4012
Hlavní autori:	Zhang, Chunjiang, Tan, Kay Chen, Lee, Loo Hay, Gao, Liang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2018 Springer Nature B.V
Predmet:	Artificial Intelligence Computational Intelligence Control Decomposition Engineering Evolutionary algorithms Genetic algorithms Interpolation Mathematical Logic and Foundations Mathematical programming Mechatronics Methodologies and Application Methods Multiple objective analysis Optimization Robotics Sparsity Adjust weight vector Multi-objective evolutionary algorithm (MOEA) MOEA/D Discontinuous Pareto fronts
ISSN:	1432-7643, 1433-7479
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Abstract	Multi-objective evolutionary algorithm based on decomposition (MOEA/D) is a recently proposed algorithm which is a research focus in the field of multi-objective evolutionary optimization. It decomposes a multi-objective problem into subproblems by mathematic programming methods and applies evolutionary algorithms to optimize the subproblems simultaneously. MOEA/D is good at finding Pareto solutions which are evenly distributed. However, it can be improved for problems with discontinuous Pareto fronts (PF). Many solutions will assemble in breakpoints in this situation. A method for adjusting weight vectors for bi-objective optimization problems with discontinuous PF is proposed. Firstly, this method detects the weight vectors which need to be adjusted using a property of MOEA/D. Secondly, the reserved vectors are divided into several subsets. Thirdly, after calculating the ideal number of vectors in each subset, vectors are adjusted evenly. Lastly, the corresponding solutions are updated by a linear interpolation. Numerical experiment shows the proposed method obtains good diversity and convergence on approached PF.
AbstractList	Multi-objective evolutionary algorithm based on decomposition (MOEA/D) is a recently proposed algorithm which is a research focus in the field of multi-objective evolutionary optimization. It decomposes a multi-objective problem into subproblems by mathematic programming methods and applies evolutionary algorithms to optimize the subproblems simultaneously. MOEA/D is good at finding Pareto solutions which are evenly distributed. However, it can be improved for problems with discontinuous Pareto fronts (PF). Many solutions will assemble in breakpoints in this situation. A method for adjusting weight vectors for bi-objective optimization problems with discontinuous PF is proposed. Firstly, this method detects the weight vectors which need to be adjusted using a property of MOEA/D. Secondly, the reserved vectors are divided into several subsets. Thirdly, after calculating the ideal number of vectors in each subset, vectors are adjusted evenly. Lastly, the corresponding solutions are updated by a linear interpolation. Numerical experiment shows the proposed method obtains good diversity and convergence on approached PF.
Author	Gao, Liang Tan, Kay Chen Lee, Loo Hay Zhang, Chunjiang
Author_xml	– sequence: 1 givenname: Chunjiang surname: Zhang fullname: Zhang, Chunjiang organization: The State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, School of Electrical and Electronic Engineering, Nanyang Technological University – sequence: 2 givenname: Kay Chen surname: Tan fullname: Tan, Kay Chen organization: Department of Computer Science, City University of Hong Kong – sequence: 3 givenname: Loo Hay surname: Lee fullname: Lee, Loo Hay organization: Department of Industrial and Systems Engineering, National University of Singapore – sequence: 4 givenname: Liang surname: Gao fullname: Gao, Liang email: gaoliang@mail.hust.edu.cn organization: The State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology
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Snippet	Multi-objective evolutionary algorithm based on decomposition (MOEA/D) is a recently proposed algorithm which is a research focus in the field of...
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SubjectTerms	Artificial Intelligence Computational Intelligence Control Decomposition Engineering Evolutionary algorithms Genetic algorithms Interpolation Mathematical Logic and Foundations Mathematical programming Mechatronics Methodologies and Application Methods Multiple objective analysis Optimization Robotics Sparsity
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Title	Adjust weight vectors in MOEA/D for bi-objective optimization problems with discontinuous Pareto fronts
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