文章基本信息

标题：A New Threshold Based Penalty Function Embedded MOEA/D
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作者：Muhammad Asif Jan ; Nasser Mansoor Tairan ; Rashida Adeeb Khanum 等
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2016
卷号：7
期号：2
DOI：10.14569/IJACSA.2016.070281
出版社：Science and Information Society (SAI)
摘要：Recently, we proposed a new threshold based penalty function. The threshold dynamically controls the penalty to infeasible solutions. This paper implants the two different forms of the proposed penalty function in the multiobjective evo-lutionary algorithm based on decomposition (MOEA/D) frame-work to solve constrained multiobjective optimization problems. This led to a new algorithm, denoted by CMOEA/D-DE-ATP. The performance of CMOEA/D-DE-ATP is tested on hard CF-series test instances in terms of the values of IGD-metric and SC-metric. The experimental results are compared with the three best performers of CEC 2009 MOEA competition. Experimental results show that the proposed penalty function is very promising, and it works well in the MOEA/D framework.
关键词：thesai; IJACSA; thesai.org; journal; IJACSA papers; Constrained multiobjective optimization; decompo-sition; MOEA/D; penalty function; threshold