Agent-based heuristics model for measuring customer disruption impact on production and inventory replenishment


Agent-based simulation approach in production and inventory environment is capable of responding and adapting to disruptions caused by customers’ changing requirements. The impacts of disruptions in production and inventory systems can be measured through learning and decision-making ability of system agents. In this paper, agent-based modelling integrated with heuristic optimisation approach is presented as embedded within a scheduling and rescheduling framework. The proposed approach is implemented in a disrupted OEMs parts manufacturing system. The integration of the framework modules in connection with inventory control helped production planners to manage disruptions by tracking order processing times and quantities and for performance measurement. The proposed approach is compared with the few existing related methods like the sequential method. The proposed approach not only revealed the impact of disruptions in terms of process times and order quantities but offered ‘available times’ which were applied for production support and inventory replenishment. This demonstrates a valuable and viable resolution strategy responding and adapting to disruptions caused by customers.

Publication DOI:
Divisions: College of Business and Social Sciences > Aston Business School
College of Business and Social Sciences > Aston Business School > Operations & Information Management
Additional Information: Publisher Copyright: Copyright © 2022 Inderscience Enterprises Ltd.
Uncontrolled Keywords: agent-based simulation,customer disruption impact,heuristics optimisation,inventory replenishment,OEM environment,production scheduling,Control and Systems Engineering,Industrial and Manufacturing Engineering
Publication ISSN: 1748-5045
Last Modified: 08 Dec 2023 12:19
Date Deposited: 30 Jan 2023 14:27
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://www.ind ... hp?artid=122244 (Publisher URL)
PURE Output Type: Article
Published Date: 2022-04-08
Accepted Date: 2020-03-29
Authors: Al-Bazi, Ammar (ORCID Profile 0000-0002-5057-4171)
Adediran, Tunde V.



Version: Accepted Version

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