水准点(测量)
一套
计算机科学
元启发式
基线(sea)
排名(信息检索)
测试套件
数学优化
人工智能
机器学习
测试用例
数学
地理
考古
回归分析
地质学
海洋学
历史
大地测量学
作者
Abhishek Kumar,Guohua Wu,Mostafa Z. Ali,Qizhang Luo,Rammohan Mallipeddi,Ponnuthurai Nagaratnam Suganthan,Swagatam Das
标识
DOI:10.1016/j.swevo.2021.100961
摘要
Generally, Synthetic Benchmark Problems (SBPs) are utilized to assess the performance of metaheuristics. However, these SBPs may include various unrealistic properties. As a consequence, performance assessment may lead to underestimation or overestimation. To address this issue, few benchmark suites containing real-world problems have been proposed for all kinds of metaheuristics except for Constrained Multi-objective Metaheuristics (CMOMs). To fill this gap, we develop a benchmark suite of Real-world Constrained Multi-objective Optimization Problems (RWCMOPs) for performance assessment of CMOMs. This benchmark suite includes 50 problems collected from various streams of research. We also present the baseline results of this benchmark suite by using state-of-the-art algorithms. Besides, for comparative analysis, a ranking scheme is also proposed.
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