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Sensitivity Analysis and Optimization for Selected Supply Chain Management Issues in the Company – Using System Dynamics and Vensim

Author

Listed:
  • Elżbieta Kasperska

    (Silesian University of Technology)

  • Elwira Mateja-Losa

    (Silesian University of Technology)

  • Rafał Marjasz

    (Silesian University of Technology)

Abstract

The aim of our paper is to present the new results of research work on optimization and simulation for some logistic problems in the company. The System Dynamics (SD) method and the Vensim simulation language are applied in order to solve specific managerial problems described by Forrester in the model of supply chain. The historical model of Customer-Producer-Employment System by Forrester (Forrester, 1961) has not been examined with the sensitivity analysis, from the “automatic” testing perspective. Optimization experiments have not been conducted, either. It is surprising, since the model is old and widely known. The opportunities offered by the Vensim language allow us to perform such analysis. The visualization called “confidence bounds“ is used, to show the behaviour of chosen variables over a period of time. The Monte-Carlo method is applied for sampling a set of numbers from within bounded domains (distribution for each searching parameters is specified). The authors of this paper conducted numerous experiments in this scope. This paper presents their results and offers some conclusions formulated at the end.

Suggested Citation

  • Elżbieta Kasperska & Elwira Mateja-Losa & Rafał Marjasz, 2013. "Sensitivity Analysis and Optimization for Selected Supply Chain Management Issues in the Company – Using System Dynamics and Vensim," Journal of Entrepreneurship, Management and Innovation, Fundacja Upowszechniająca Wiedzę i Naukę "Cognitione", vol. 9(2), pages 29-44.
    • Handle: RePEc:aae:journl:v:9:y:2013:i:2:p:29-44
    DOI: 10.7341/2013922
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    Cited by:

    1. Chai, Naijie & Zhou, Wenliang & Hu, Xinlei, 2022. "Safety evaluation of urban rail transit operation considering uncertainty and risk preference: A case study in China," Transport Policy, Elsevier, vol. 125(C), pages 267-288.

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