Abstract
E-commerce supply chains are becoming more complex due to increasing global sales, and product returns from these sales are alarmingly high, highlighting the importance of effective return management. This paper proposes a reverse logistics network model to optimize return management. The proposed model applies ward-like hierarchical clustering with geographical constraints to detect return tendencies and utilizes mixed integer linear programming to optimize the network. The decision variables of the model include selection of Initial Collection Centers (ICCs), allocation of customer markets to ICCs, and optimal return volumes to be sent to each fulfillment center and recycling center from ICCs. The validity of the proposed model is established through a case study conducted in the consumer electrical and electronics sector of an e-commerce firm, providing 39.9% cost savings on average compared to the current Reverse Logistics (RL) network operation. This study contributes to the literature by integrating industry 4.0 technologies into the assessment of RL and facility planning with network optimization. The proposed RL network model serves as an operational planning tool, providing directions to e-commerce firms on optimizing RL networks and utilizing partner networks with integrated decision making for product returns.
Original language | English |
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Book series | IFAC-PapersOnLine |
Volume | 56 |
Issue number | 2 |
Pages (from-to) | 138-143 |
Number of pages | 6 |
ISSN | 1474-6670 |
DOIs | |
Publication status | Published - 1 Jul 2023 |
Event | 22nd IFAC World Congress - Yokohama, Japan Duration: 9 Jul 2023 → 14 Jul 2023 |
Conference
Conference | 22nd IFAC World Congress |
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Country/Territory | Japan |
City | Yokohama |
Period | 09/07/2023 → 14/07/2023 |
Sponsor | Azbil Corporation, et al., Fujita Corporation, Hitachi, Ltd., Kumagai Gumi Co., Ltd., The Society of Instrument and Control Engineers (SICE) |
Bibliographical note
Publisher Copyright:Copyright © 2023 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
Keywords
- Facility planning and materials handling
- Industry 4.0
- Logistics in manufacturing
- Operations research
- Supply chains and networks
- Sustainable Manufacturing