Replicated Computational Results (RCR) Report for“A Practical Approach to Subset Selection for Multi-Objective Optimization via Simulation”
该报告验证了Currie和Monks提出的两阶段多目标仿真优化算法，通过复现其Python代码确认了原文结果，适用于仿真优化研究者。
In “A Practical Approach to Subset Selection for Multi-Objective Optimization via Simulation,” Currie and Monks propose an algorithm for multi-objective simulation-based optimization. In contrast to sequential ranking and selection schemes, their algorithm follows a two-stage scheme. The approach is evaluated by comparing the results to those obtained using the existing OCBA-m algorithm for synthetic problems and for a hospital ward configuration problem. The authors provide the Python code used in the experiments in the form of Jupyter notebooks. The code successfully reproduced the results shown in the article.