Dynamic diversity preservation strategy for multi-objective evolutionary algorithms

Computer Engineering and Applications ›› 2012, Vol. 48 ›› Issue (2): 48-52.

• 研究、探讨 • Previous Articles Next Articles

Dynamic diversity preservation strategy for multi-objective evolutionary algorithms

PANG Shan1, YANG Xinyi2, SU Qingtang1

1.College of Information Science and Engineering, Ludong University, Yantai, Shandong 264025, China
2.Department of Aircraft Engineering, Naval Aeronautical and Astronautical University, Yantai, Shandong 264001, China

Received:1900-01-01 Revised:1900-01-01 Online:2012-01-11 Published:2012-01-11

提高多目标进化算法分布性的动态调整机制

逄珊1，杨欣毅2，苏庆堂1

1.鲁东大学信息科学与工程学院，山东烟台 264025
2.海军航空工程学院飞行器工程系，山东烟台 264001

Abstract

Abstract: In order to improve diversity performance of multi objective evolutionary algorithms, a new dynamic diversity preservation strategy based on polar coordinates is proposed. Each solution is assigned a contract-expand coefficient which is related to its distribution in polar coordinates. This coefficient is used to adjust Pareto dominance in solutions set dynamically during evolution. Sparsely distributed solutions are evaluated in terms of Pareto dominance relation, which in turn improve the distribution of solutions set. Results show that the proposed strategy is able to improve conventional MOEAs on their diversity performance, at the same time, maintain convergence to Pareto optimal front on the same level.

Key words: multi-objective optimization, evolutionary algorithms, Pareto dominance, polar coordinates, diversity

摘要： 为提高多目标进化算法的分布性，提出一种基于极坐标的动态调整机制。在极坐标下，根据解集的拥挤程度，计算个体解的缩放系数。在进化过程中利用该缩放系数动态调整解集支配关系，适当提高分布性好的解在支配关系中的地位以改善解的分布。对测试函数的仿真试验结果表明，将该机制应用于经典算法能显著提高算法的分布性，同时保持良好的收敛性。

关键词: 多目标优化, 进化算法, 支配关系, 极坐标, 多样性

PANG Shan1, YANG Xinyi2, SU Qingtang1. Dynamic diversity preservation strategy for multi-objective evolutionary algorithms[J]. Computer Engineering and Applications, 2012, 48(2): 48-52.

逄珊1，杨欣毅2，苏庆堂1. 提高多目标进化算法分布性的动态调整机制[J]. 计算机工程与应用, 2012, 48(2): 48-52.

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Dynamic diversity preservation strategy for multi-objective evolutionary algorithms

提高多目标进化算法分布性的动态调整机制

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