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 b...
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Format: | Article |
Language: | English |
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University of Novi Sad, Faculty of Technical Sciences
2022-12-01
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Series: | International Journal of Industrial Engineering and Management |
Subjects: | |
Online Access: | http://www.ijiemjournal.uns.ac.rs/images/journal/volume13/IJIEM_318.pdf |
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author | Tunde Adediran Ammar Al-Bazi |
author_facet | Tunde Adediran Ammar Al-Bazi |
author_sort | Tunde Adediran |
collection | DOAJ |
description | 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. The proposed method outperformed
the sequential and instantaneous methods in terms of the total number of late or unsatisfied
orders as well as the level of overall inventory sustainability as impacted by disruptions. |
first_indexed | 2024-04-12T00:51:19Z |
format | Article |
id | doaj.art-3a09ce15d9214aad90165c7da85a962b |
institution | Directory Open Access Journal |
issn | 2217-2661 2683-345X |
language | English |
last_indexed | 2024-04-12T00:51:19Z |
publishDate | 2022-12-01 |
publisher | University of Novi Sad, Faculty of Technical Sciences |
record_format | Article |
series | International Journal of Industrial Engineering and Management |
spelling | doaj.art-3a09ce15d9214aad90165c7da85a962b2022-12-22T03:54:44ZengUniversity of Novi Sad, Faculty of Technical SciencesInternational Journal of Industrial Engineering and Management2217-26612683-345X2022-12-01134265282http://doi.org/10.24867/IJIEM-2022-3-318318Complex Production-Inventory Replenishment Problem With Uncertainty in Customer BehaviourTunde Adediran0Ammar Al-BaziAston University, Birmingham B4 7ET, United KingdomA 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. The proposed method outperformed the sequential and instantaneous methods in terms of the total number of late or unsatisfied orders as well as the level of overall inventory sustainability as impacted by disruptions.http://www.ijiemjournal.uns.ac.rs/images/journal/volume13/IJIEM_318.pdfproduction schedulinguncertainty in customer behaviourproduction disruptionoem manufacturergradual inventory replenishment policyheuristics optimisationagent-based modelling |
spellingShingle | Tunde Adediran Ammar Al-Bazi Complex Production-Inventory Replenishment Problem With Uncertainty in Customer Behaviour International Journal of Industrial Engineering and Management production scheduling uncertainty in customer behaviour production disruption oem manufacturer gradual inventory replenishment policy heuristics optimisation agent-based modelling |
title | Complex Production-Inventory Replenishment Problem With Uncertainty in Customer Behaviour |
title_full | Complex Production-Inventory Replenishment Problem With Uncertainty in Customer Behaviour |
title_fullStr | Complex Production-Inventory Replenishment Problem With Uncertainty in Customer Behaviour |
title_full_unstemmed | Complex Production-Inventory Replenishment Problem With Uncertainty in Customer Behaviour |
title_short | Complex Production-Inventory Replenishment Problem With Uncertainty in Customer Behaviour |
title_sort | complex production inventory replenishment problem with uncertainty in customer behaviour |
topic | production scheduling uncertainty in customer behaviour production disruption oem manufacturer gradual inventory replenishment policy heuristics optimisation agent-based modelling |
url | http://www.ijiemjournal.uns.ac.rs/images/journal/volume13/IJIEM_318.pdf |
work_keys_str_mv | AT tundeadediran complexproductioninventoryreplenishmentproblemwithuncertaintyincustomerbehaviour AT ammaralbazi complexproductioninventoryreplenishmentproblemwithuncertaintyincustomerbehaviour |