An R2 Indicator and Decomposition Based Steady-State Evolutionary Algorithm for Many-Objective Optimization
Joint Authors
Shi, Huaitao
Li, Fei
Liu, Jianchang
Huang, Peiqiu
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-03-11
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Abstract EN
An R2 indicator based selection method is a major ingredient in the formulation of indicator based evolutionary multiobjective optimization algorithms.
The existing classical indicator based selection methodologies have demonstrated an excellent performance to solve low-dimensional optimization problems.
However, the R2 indicator based evolutionary multiobjective optimization algorithms encounter enormous challenges in high-dimensional objective space.
Our main purpose is to explore how to extend the R2 indicator to handle many-objective optimization problems.
After analyzing the R2 indicator, the objective space partition strategy, and the decomposition method, we propose a steady-state evolutionary algorithm based on the R2 indicator and the decomposition method, named, R2-MOEA/D, to obtain well-converged and well-distributed Pareto front.
The main contribution of this paper contains two aspects.
(1) The convergence and diversity for the R2 indicator based selection are analyzed.
Two improper selection situations will be properly solved via applying the decomposition method.
(2) According to the position of a new individual in the steady-state evolutionary algorithm, two different objective space partition strategies and the corresponding selection methods are proposed.
Extensive experiments are conducted on a variety of benchmark test problems, and the experimental results demonstrate that the proposed algorithm has competitive performance in comparison with several tailored algorithms for many-objective optimization.
American Psychological Association (APA)
Li, Fei& Liu, Jianchang& Huang, Peiqiu& Shi, Huaitao. 2018. An R2 Indicator and Decomposition Based Steady-State Evolutionary Algorithm for Many-Objective Optimization. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-18.
https://search.emarefa.net/detail/BIM-1205603
Modern Language Association (MLA)
Li, Fei…[et al.]. An R2 Indicator and Decomposition Based Steady-State Evolutionary Algorithm for Many-Objective Optimization. Mathematical Problems in Engineering No. 2018 (2018), pp.1-18.
https://search.emarefa.net/detail/BIM-1205603
American Medical Association (AMA)
Li, Fei& Liu, Jianchang& Huang, Peiqiu& Shi, Huaitao. An R2 Indicator and Decomposition Based Steady-State Evolutionary Algorithm for Many-Objective Optimization. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-18.
https://search.emarefa.net/detail/BIM-1205603
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1205603