4.7 Article

A Benchmark-Suite of real-World constrained multi-objective optimization problems and some baseline results

期刊

SWARM AND EVOLUTIONARY COMPUTATION
卷 67, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.swevo.2021.100961

关键词

Metaheuristics; Performance assessment; Real-World problems; Multi-Objective constrained optimization; Benchmark-Suite; Ranking scheme

资金

  1. Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education [2021R111A3049810]

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The article introduces a new benchmark suite RWCMOPs for assessing the performance of Constrained Multi-objective Metaheuristics, consisting of 50 real-world problems and proposing a ranking scheme for comparative analysis.
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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