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A Novel Ranking Method Based on Subjective Probability Theory for Evolutionary Multiobjective Optimization

机译：基于主观概率理论的进化多目标优化排序新方法

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摘要

Most of the engineering problems are modeled as evolutionary multiobjective optimization problems, but they always ask for only one best solution, not a set of Pareto optimal solutions. The decision maker's subjective information plays an important role in choosing the best solution from several Pareto optimal solutions. Generally, the decision-making processing is implemented after Pareto optimality. In this paper, we attempted to incorporate the decider's subjective sense with Pareto optimality for chromosomes ranking. A new ranking method based on subjective probability theory was thus proposed in order to explore and comprehend the true nature of the chromosomes on the Pareto optimal front. The properties of the ranking rule were proven, and its transitivity was presented as well. Simulation results compared the performance of the proposed ranking approach with the Pareto-based ranking method for two multiobjective optimization cases, which demonstrated the effectiveness of the new ranking approach.
机译：大多数工程问题都被建模为进化多目标优化问题，但它们始终只要求一个最佳解决方案，而不是一组Pareto最佳解决方案。决策者的主观信息在从多个Pareto最佳解决方案中选择最佳解决方案方面发挥着重要作用。通常，决策处理是在帕累托最优之后进行的。在本文中，我们尝试将决策者的主观感觉与帕累托最优相结合，以进行染色体排名。因此，提出了一种基于主观概率理论的新排序方法，以探索和理解帕累托最优前沿染色体的真实性质。证明了排序规则的性质，并介绍了其传递性。仿真结果将建议的排序方法与基于Pareto的排序方法在两个多目标优化情况下的性能进行了比较，证明了该新排序方法的有效性。

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  • 来源
    《Mathematical Problems in Engineering》 |2011年第3期|p.1-10|共10页
  • 作者

    Shuang Wei; Henry Leung;

  • 作者单位

    Department of Electrical and Computer Engineering, University of Calgary, Calgary, AB, Canada T2N 1N4;

    Department of Electrical and Computer Engineering, University of Calgary, Calgary, AB, Canada T2N 1N4;

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