A Tutorial on Combining Flexsim with Python for Developing Discrete-Event Simheuristics

Connecting commercial discrete-event simulation packages to external software or programming languages is essential to advance simulation modeling capabilities. For instance, this connectivity allows users to link the simulation environment to metaheuristic optimization algorithms or to machine lear...

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Bibliographic Details
Published inProceedings - Winter Simulation Conference pp. 1386 - 1400
Main Authors Leon, Jonas F., Marone, Paolo, Peyman, Mohammad, Li, Yuda, Calvet, Laura, Dehghanimohammadabadi, Mohammad, Juan, Angel A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 11.12.2022
Subjects
Machine learning algorithms
Metaheuristics
Software
Software algorithms
Stochastic systems
Transportation
Tutorials
Online AccessGet full text
ISSN1558-4305
DOI10.1109/WSC57314.2022.10015309

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Summary:Connecting commercial discrete-event simulation packages to external software or programming languages is essential to advance simulation modeling capabilities. For instance, this connectivity allows users to link the simulation environment to metaheuristic optimization algorithms or to machine learning methods. However, implementing these connections is not a trivial task, and may require API access and proper settings configurations. This tutorial provides a step-by-step guideline to connect the FlexSim commercial simulator with the popular Python programming language via sockets. Using this type of connection, a simheuristic algorithm coded in Python aims at optimizing the product allocation in a warehouse, which has been previously modeled in the aforementioned simulator. In addition, potential future applications of this software combination will be discussed to provide insights into future developments such as more advanced simheuristics or combinations of simulation with learnheuristics.
ISSN:1558-4305
DOI:10.1109/WSC57314.2022.10015309