Journal of Computer Applications ›› 2010, Vol. 30 ›› Issue (4): 997-999.

• Artificial intelligence • Previous Articles     Next Articles

Quick multi-objective evolutionary algorithm based on adaptive Pareto-ε dominance

  

  • Received:2009-10-19 Revised:2009-12-06 Online:2010-04-15 Published:2010-04-01
  • Contact: WANG Jiang-qing

基于Pareto-ε优胜的自适应快速多目标演化算法

王江晴1,杨勋2   

  1. 1. 中南民族大学计算机科学学院
    2.
  • 通讯作者: 王江晴
  • 基金资助:
    复杂环境下动态车辆路径问题的建模与优化

Abstract: For Multi-objective Optimization Problems (MOP), it is very important to provide proper and feasible solutions rapidly for the decision makers. A method for MOP was given. First, a concept of Pareto-ε dominance was defined. Then, based on this concept, a new adaptive multi-objective evolutionary algorithm was proposed. The simulation results demonstrate that the new algorithm can improve the process of MOP optimization, and can meet the requirements of high-speed and effectiveness in application.

Key words: multi-objective optimization, Pareto dominance, Pareto front, evolutionary algorithm, adaptive

摘要: 在多目标优化领域,如何快速地为决策者提供合理、可行的解决方案尤为重要,为此,给出了多目标优化问题的一种新解法。定义了一种Pareto-ε优胜关系的概念,将此概念引入多目标优化问题中,设计了一种新的基于ε-优胜的自适应快速多目标演化算法。计算机仿真表明,该算法可以明显改善求解多目标优化问题时的寻优过程,能适应实际应用环境下快速、有效的决策要求。

关键词: 多目标优化, Pareto优胜, Pareto前沿, 演化算法, 自适应