A practical methodology for reproducible experimentation: an application to the Double-row Facility Layout Problem

Author:

Martín-Santamaría Raúl1,Cavero Sergio2,Herrán Alberto3,Duarte Abraham4,Colmenar J. Manuel5

Affiliation:

1. Department of Computer Science and Statistics, Universidad Rey Juan Carlos, Móstoles, 28933, Spain raul.martin@urjc.es

2. Department of Computer Science and Statistics, Universidad Rey Juan Carlos, Móstoles, 28933, Spain sergio.cavero@urjc.es

3. Department of Computer Science and Statistics, Universidad Rey Juan Carlos, Móstoles, 28933, Spain alberto.herran@urjc.es

4. Department of Computer Science and Statistics, Universidad Rey Juan Carlos, Móstoles, 28933, Spain abraham.duarte@urjc.es

5. Department of Computer Science and Statistics, Universidad Rey Juan Carlos, Móstoles, 28933, Spain josemanuel.colmenar@urjc.es

Abstract

Abstract Reproducibility of experiments is a complex task in stochastic methods such as evolutionary algorithms or metaheuristics in general. Many works from the literature give general guidelines to favor reproducibility. However, none of them provide both a practical set of steps and also software tools to help on this process. In this paper, we propose a practical methodology to favor reproducibility in optimization problems tackled with stochastic methods. This methodology is divided into three main steps, where the researcher is assisted by software tools which implement state-of-theart techniques related to this process. The methodology has been applied to study the Double Row Facility Layout Problem, where we propose a new algorithm able to obtain better results than the state-of-the-art methods. To this aim, we have also replicated the previous methods in order to complete the study with a new set of larger instances. All the produced artifacts related to the methodology and the study of the target problem are available in Zenodo.

Publisher

MIT Press

Subject

Computational Mathematics

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. On the automatic generation of metaheuristic algorithms for combinatorial optimization problems;European Journal of Operational Research;2024-11

2. A GRASP method for the Bi-Objective Multiple Row Equal Facility Layout Problem;Applied Soft Computing;2024-09

3. Multi-objective general variable neighborhood search for software maintainability optimization;Engineering Applications of Artificial Intelligence;2024-07

4. Energy optimization approach for the Single-Row Facility Layout Problem;2024 IEEE 15th International Colloquium on Logistics and Supply Chain Management (LOGISTIQUA);2024-05-02

5. Iterated Local Search for the Facility Location Problem with Limited Choice Rule;Lecture Notes in Computer Science;2024

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