Complex Production-Inventory Replenishment Problem with Uncertainty in Customer Behaviour


A flow-shop production-inventory system can become very complex in terms of production planning and scheduling. One of the causes of complexity in such a system is the uncertainty of customer demand behaviour which disrupts production lines and inventory control. The uncertainty in customer demand behaviour that causes production disruptions can be in the form of order cancellation, change in order delivery sequence and due time. In general, such disruptions cause order shortages, late order delivery, and the underperformance of resources, amongst others. This paper considers the random combination of occurrences of these disruptions under different production scenario problems. An innovative framework that embeds agent-based simulation, heuristic algorithm, and inventory replenishment strategy is proposed to tackle these disruption problems. The integration of these methods formed a robust platform for adapting and accommodating disruptions with minimum impact on production operations. An experimental study is performed, and the results determine the impact of disruptions under different demand and inventory statuses. An inventory replenishment method is compared with sequential and instantaneous replenishment methods to establish the significance of the proposed method.

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: © 2022, International Journal of Industrial Engineering and Management. All Rights Reserved. This is an open access article distributed under the CC BY-NC-ND 4.0 terms and conditions.
Uncontrolled Keywords: Agent-based modelling,Gradual inventory replenishment policy,Heuristics optimisation,OEM manufacturer,Production disruption,Production scheduling,Uncertainty in customer behaviour,Business, Management and Accounting (miscellaneous),Industrial and Manufacturing Engineering
Publication ISSN: 2217-2661
Last Modified: 28 Feb 2024 08:31
Date Deposited: 20 Apr 2023 09:14
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Related URLs: http://www.ijie ... 3/IJIEM_318.pdf (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2022-12
Published Online Date: 2022-12-15
Accepted Date: 2022-12-12
Authors: Adediran, Tunde V.
Al-Bazi, Dr Ammar (ORCID Profile 0000-0002-5057-4171)

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