Optimizing inventory management through multiobjective reverse logistics with environmental impact
This paper expands on Jaber and El Saadany and Hasanov et al. by distinguishing between customer perceptions of new and remanufactured (repaired) items, assuming remanufactured items are not seen as equivalent to new ones. As a new approach, our three models consider integer lot sizes for both new a...
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| Veröffentlicht in: | Applied mathematical modelling Jg. 146; S. 116166 |
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| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Elsevier Inc
01.10.2025
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| Schlagworte: | |
| ISSN: | 0307-904X |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | This paper expands on Jaber and El Saadany and Hasanov et al. by distinguishing between customer perceptions of new and remanufactured (repaired) items, assuming remanufactured items are not seen as equivalent to new ones. As a new approach, our three models consider integer lot sizes for both new and repaired items, formulating the problem as a mixed integer programming (MIP) model. Unlike previous studies, which often relied on rounding or heuristic methods that can lead to inaccuracies or infeasible solutions, our approach provides efficient algorithms and uses appropriate solvers to obtain better approximations. Additionally, by incorporating waste estimation as an environmental consideration, we extend the model's relevance to sustainable logistics, by transforming it into a multiobjective optimization problem. Numerical experiments, including comparisons with test examples from existing literature, validate the models. A detailed sensitivity analysis further explores the effects of varying setup and holding costs. We also investigate various scalarization techniques to approximate the Pareto front, which considers both inventory cost and waste estimation as objectives, giving decision-makers flexible options suited to specific requirements.
•Three mathematical models for reverse logistic inventory management and solution for mixed integer decision variables.•Multiobjective mathematical model of the reverse logistics system that considered holding cost and environmental objectives.•Analytical mathematical model, supported by numerical experimentation, to validate a real-world industry example.•Scalarization approaches and algorithms to solve a bi-objective reverse logistics model.•Approximate the Pareto solutions of the multiobjective problem. |
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| ISSN: | 0307-904X |
| DOI: | 10.1016/j.apm.2025.116166 |