Agent-Based Modelling and Heuristic Approach for Solving Complex OEM Flow-Shop Productions under Customer Disruptions

Tunde Victor Adediran, Ammar Al Bazi, Luiz Eduardo dos Santos

    Research output: Contribution to journalArticlepeer-review

    13 Citations (Scopus)
    83 Downloads (Pure)


    The application of the agent-based simulation approach in the flow-shop production environment has recently gained popularity among researchers. The concept of agent and agent functions can help to automate a variety of difficult tasks and assist decision-making in flow-shop production. This is especially so in the large-scale Original Equipment Manufacturing (OEM) industry, which is associated with many uncertainties. Among these are uncertainties in customer demand requirements that create disruptions that impact production planning and scheduling, hence, making it difficult to satisfy demand in due time, in the right order delivery sequence, and in the right item quantities. It is however important to devise means of adapting to these inevitable disruptive problems by accommodating them while minimising the impact on production performance and customer satisfaction.
    In this paper, an innovative embedded agent-based Production Disruption Inventory-Replenishment (PDIR) framework, which includes a novel adaptive heuristic algorithm and inventory replenishment strategy which is proposed to tackle the disruption problems. The capabilities and functionalities of agents are utilised to simulate the flow-shop production environment and aid learning and decision making. In practice, the proposed approach is implemented through a set of experiments conducted as a case study of an automobile parts facility for a real-life large-scale OEM. The results are presented in term of Key Performance Indicators (KPIs), such as the number of late/unsatisfied orders, to determine the effectiveness of the proposed approach. The results reveal a minimum number of late/unsatisfied orders, when compared with other approaches.
    Original languageEnglish
    Pages (from-to)29-41
    Number of pages13
    JournalComputers & Industrial Engineering
    Early online date2 May 2019
    Publication statusPublished - Jul 2019

    Bibliographical note

    NOTICE: this is the author’s version of a work that was accepted for publication in Computers & Industrial Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers & Industrial Engineering, 133 (2019)
    DOI: 10.1016/j.cie.2019.04.054

    © 2019, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International


    • Agent-based modelling
    • Heuristic algorithm
    • OEM flow-shop
    • Production disruption

    ASJC Scopus subject areas

    • Computer Science(all)
    • Engineering(all)


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