Jingxuan Wei

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— Designing efficient algorithms for difficult multi-objective optimization problems is a very challenging problem. In this paper a new clustering multi-objective evolutionary algorithm based on orthogonal and uniform design is proposed. First, the orthogonal design is used to generate initial population of points that are scattered uniformly over the(More)
The 65 papers presented were carefully reviewed and selected from 140 submissions. The topics covered are evolutionary learning; evolutionary optimisa-tion; hybrid learning; adaptive systems; theoretical issues in evolutionary computation; and real-world applications of evolutionary computation techniques.... more on http:// springer.com/978-3-540-89693-7
Developing efficient algorithms for dynamic constrained multi-objective optimization problems (DCMOPs) is very challenging. This paper describes an attraction based particle swarm optimization (PSO) algorithm with sphere search for such problems. A dynamic constrained multi-objective optimization problem is transformed into a series of static constrained(More)