Multi-Objective Memetic Algorithms
Multi-Objective Memetic Algorithms
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DOI：
10.1007/978-3-540-88051-6
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发表时间：
2009-03
期刊：
影响因子：
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通讯作者：
C. Goh;Y. Ong;K. Tan
中科院分区：
文献类型：
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作者：
C. Goh;Y. Ong;K. Tan
在这一章中，我们提出了一个混合的随机为基础的搜索方法与确定性区域分解的解决方案空间的多目标优化。在介绍算法之前，我们介绍了一个通用的配方的优化问题，适合于描述单目标和多目标问题。随机方法，基于行为主义，结合分解的解决方案的步伐进行了测试，一组标准的多目标优化问题和一个简单的，但有代表性的情况下，空间轨迹设计。
In this chapter we present a hybridization of a stochastic based search approach for multi-objective optimization with a deterministic domain decomposition of the solution space. Prior to the presentation of the algorithm we introduce a general formulation of the optimization problem that is suitable to describe both single and multi-objective problems. The stochastic approach, based on behaviorism, combined with the decomposition of the solutions pace was tested on a set of standard multi-objective optimization problems and on a simple but representative case of space trajectory design.