Strengthening the reporting of empirical simulation studies: Introducing the STRESS guidelines

This study develops a standardised checklist approach to improve the reporting of discrete-event simulation, system dynamics and agent-based simulation models within the field of Operational Research and Management Science. Incomplete or ambiguous reporting means that many simulation studies are not reproducible, leaving other modellers with an incomplete picture of what has been done and unable to judge the reliability of the results. Crucially, unclear reporting makes it difficult to reproduce or reuse findings. In this paper, we review the evidence on the quality of model reporting and consolidate previous work. We derive general good practice principles and three 20-item checklists aimed at Strengthening The Reporting of Empirical Simulation Studies (STRESS): STRESS-DES, STRESS-ABS and STRESS-SD for discrete-event simulation, agent-based simulation and system dynamics, respectively. Given the variety of simulation projects, we provide usage and troubleshooting advice to cover a wide range of situations.

本研究构建了一套标准化检查表方法，旨在优化运筹学（Operational Research）与管理科学（Management Science）领域内离散事件仿真（discrete-event simulation）、系统动力学（system dynamics）以及基于智能体仿真（agent-based simulation）三类模型的报告撰写规范。若报告内容存在缺失或表述模糊，诸多仿真研究将无法被复现，致使其他建模者难以明晰研究全貌，亦无法评判研究结果的可靠性。尤为关键的是，报告表述不清会极大阻碍研究成果的复现与复用。本文首先梳理了当前模型报告质量的相关研究证据，并整合了既往相关研究成果。本研究提出了通用的良好实践原则，以及三套各包含20个条目、旨在强化实证仿真研究报告规范（Strengthening The Reporting of Empirical Simulation Studies，缩写为STRESS）的检查表：分别对应离散事件仿真的STRESS-DES、基于智能体仿真的STRESS-ABS与系统动力学的STRESS-SD。考虑到仿真项目的多样性，本文还提供了使用指南与排障建议，以覆盖各类研究情境。