A Benchmark-Suite of real-World constrained multi-objective optimization problems and some baseline results
Swarm and Evolutionary Computation
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.
Kumar, Abhishek; Wu, Guohua; Ali, Mostafa Z.; Luo, Qizhang; Mallipeddi, Rammohan; Suganthan, Ponnuthurai Nagaratnam; and Das, Swagatam, "A Benchmark-Suite of real-World constrained multi-objective optimization problems and some baseline results" (2021). Journal Articles. 1690.