ADEMO/D: Multiobjective optimization by an adaptive differential evolution algorithm
ADEMO/D: Multiobjective optimization by an adaptive differential evolution algorithm
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DOI：
10.1016/j.neucom.2013.06.043
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发表时间：
2014-03
期刊：
影响因子：
6
通讯作者：
Sandra M. Venske;Richard A. Gonçalves;M. Delgado
中科院分区：
文献类型：
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作者：
Sandra M. Venske;Richard A. Gonçalves;M. Delgado
本文提出了一种多目标问题的自适应差分进化方法（ADEMO/D）。该方法结合了基于分解的多目标进化算法（MOEA/D）的概念和策略适应机制。在这项工作中，我们测试了两种执行自适应策略选择的方法：概率匹配（PM）和自适应追踪（AP）。结合四种基于相对适应度改进的信用分配技术对PM和AP进行了分析。DE策略根据概率从候选池中选择，该概率取决于其先前生成有希望的解决方案的经验。在实验中，我们评估了所提出方法的某些特征，考虑了八种不同的版本，同时解决了一组由10个多目标优化问题实例组成的完善集。接下来，目前最好的版本（ADEMO/D）将面对其非自适应版本。最后，在相同的应用环境下，将ADEMO/D算法与四种重要的多目标优化算法进行比较。采用帕累托顺应指标和统计检验来评价算法的性能。初步结果很有希望，表明ADEMO/D是目前最先进的多目标优化的候选方法。
This paper presents an approach for continuous optimization called Adaptive Differential Evolution for Multiobjective Problems (ADEMO/D). The approach incorporates concepts of Multiobjective Evolutionary Algorithms based on Decomposition (MOEA/D) and mechanisms of strategies adaptation. In this work we test two methods to perform adaptive strategy selection: Probability Matching (PM) and Adaptive Pursuit (AP). PM and AP are analyzed in combination with four credit assignment techniques based on relative fitness improvements. The DE strategy is chosen from a candidate pool according to a probability that depends on its previous experience in generating promising solutions. In experiments, we evaluate certain features of the proposed approach, considering eight different versions while solving a well established set of 10 instances of Multiobjective Optimization Problems. Next the best-so-far version (ADEMO/D) is confronted with its non-adaptive counterparts. Finally ADEMO/D is compared with four important multiobjective optimization algorithms in the same application context. Pareto compliant indicators and statistical tests are applied to evaluate the algorithm performances. The preliminary results are very promising and stand ADEMO/D as a candidate to the state-of-the-art for multiobjective optimization.