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| Co-evolutionary Multi-objective Optimization Algorithm with Polymorphous Populations |
| CHEN Zhen-Xing, YAN Xuan-Hui, WU Kun-An |
| College of Mathematics and Computer Science, Fujian Normal University, Fuzhou 350007 |
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Abstract To improve the diversity maintenance ability of evolutionary multi-objective optimization algorithms and obtain a set of better distributed non-dominated solutions, a co-evolutionary multi-objective optimization algorithm with polymorphous populations is proposed. Firstly, a co-evolutionary frame of polymorphous populations is designed. Next, by introducing the minimum vectorial angle which is capable of measuring the similarity between different Pareto-ranked solutions, a selection strategy for suboptimum non-dominated solutions is proposed to enhance the diversity of populations. Finally, a population removal strategy based on an ordered link-list is put forward. Thus, the uniformity and the spread of the solutions are improved. Compared with some typical algorithms, the proposed algorithm has good convergence and remains a better diversity and uniformity.
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Received: 09 September 2013
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2014, Vol. 27 
