Many-Objective Optimization Using Adaptive Differential Evolution with a New Ranking Method
Xiaoguang He,Cai Dai,Zehua Chen +2 more
TL;DR: A new ranking method is proposed for many-objective optimization problems to verify a relatively smaller number of representative nondominated solutions with a uniform and wide distribution and improve the selection pressure of MOEAs.
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Abstract: Pareto dominance is an important concept and is usually used in multiobjective evolutionary algorithms (MOEAs) to determine the nondominated solutions. However, for many-objective problems, using Pareto dominance to rank the solutions even in the early generation, most obtained solutions are often the nondominated solutions, which results in a little selection pressure of MOEAs toward the optimal solutions. In this paper, a new ranking method is proposed for many-objective optimization problems to verify a relatively smaller number of representative nondominated solutions with a uniform and wide distribution and improve the selection pressure of MOEAs. After that, a many-objective differential evolution with the new ranking method (MODER) for handling many-objective optimization problems is designed. At last, the experiments are conducted and the proposed algorithm is compared with several well-known algorithms. The experimental results show that the proposed algorithm can guide the search to converge to the true PF and maintain the diversity of solutions for many-objective problems.
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Citations
Many-objective differential evolution optimization based on reference points: NSDE-R
TL;DR: The proposed NSDE-R algorithm was applied to test problems from the DTLZ and WFG suite and has shown to have a higher rate of convergence and better convergence to the analytical Pareto front.
14
Many-Objective Flexible Job Shop Scheduling Problem with Green Consideration
Yanwei Sang,Jianping Tan +1 more
TL;DR: Wang et al. as discussed by the authors proposed a many-objective flexible job shop scheduling model, which combines an improved strength Pareto evolution method (SPEA2) and the variable neighborhood search method.
A new hypervolume-based differential evolution algorithm for many-objective optimization
TL;DR: In MODEhv, a modified differential evolution paradigm with automatic parameter configuration strategy is used to balance exploration and exploitation of the algorithm, and the hypervolume indicator is incorporated for the selection of solutions to be varied and Solutions to be kept in archive respectively.
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An Indicator and Decomposition Based Steady-State Evolutionary Algorithm for Many-Objective Optimization
TL;DR: A steady-state evolutionary algorithm based on the indicator and the decomposition method, named, -MOEA/D, is proposed to obtain well-converged and well-distributed Pareto front and has competitive performance in comparison with several tailored algorithms for many-objective optimization.
An Improvement Evolutionary Algorithm Based on Decomposition and Grid-based Pareto Dominance for Many-objective Optimization
Xiaoguang He,Cai Dai +1 more
- 01 Jul 2022
TL;DR: An better evolutionary algorithm based on decomposition and grid-based Pareto dominance (MOEA/DG) is proposed to work out many-objective optimization problems to heighten the convergence and diversity by generating good offspring with a good selection strategy.
References
A fast and elitist multiobjective genetic algorithm: NSGA-II
TL;DR: This paper suggests a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties, and modify the definition of dominance in order to solve constrained multi-objective problems efficiently.
Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces
Rainer Storn,Kenneth Price +1 more
TL;DR: In this article, a new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented, which requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.
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Principles and Procedures of Statistics: A Biometrical Approach
Robert G. D. Steel,James H. Torrie +1 more
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TL;DR: Observations probability sampling from a normal distribution comparisons involving two sample means principles of experimental design analysis of variance.
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