Replicated Computational Results (RCR) Report for“A Practical Approach to Subset Selection for Multi-Objective Optimization via Simulation”

2021 ◽  
Vol 31 (4) ◽  
pp. 1-2
Author(s):  
Philipp Andelfinger

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.

2021 ◽  
Vol 31 (4) ◽  
pp. 1-15
Author(s):  
Christine S. M. Currie ◽  
Thomas Monks

We describe a practical two-stage algorithm, BootComp, for multi-objective optimization via simulation. Our algorithm finds a subset of good designs that a decision-maker can compare to identify the one that works best when considering all aspects of the system, including those that cannot be modeled. BootComp is designed to be straightforward to implement by a practitioner with basic statistical knowledge in a simulation package that does not support sequential ranking and selection. These requirements restrict us to a two-stage procedure that works with any distributions of the outputs and allows for the use of common random numbers. Comparisons with sequential ranking and selection methods suggest that it performs well, and we also demonstrate its use analyzing a real simulation aiming to determine the optimal ward configuration for a UK hospital.


SIMULATION ◽  
2019 ◽  
Vol 96 (1) ◽  
pp. 3-15 ◽  
Author(s):  
Wang Li ◽  
Zhu Xiaoning ◽  
Xie Zhengyu

An efficient container stacking approach is vital to the handling efficiency of container transshipment terminals. In this paper, by considering container allocation preferences and operation distance, the container stacking problem in rail–truck transshipment terminals has been formulated as a multi-objective optimization model to minimize container overlapping amounts and crane moving distance. A simulation-based algorithm implementing process has been developed to stack containers to the optimum positions. Computational experiments on data from a rail–truck transshipment terminal in China are conducted to test the efficiency of the proposed approach. Experimental results demonstrate that the container stacking approach is efficient and significant for improving handling efficiency in rail–truck transshipment terminals.


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