Multi-objective modelling of sustainable closed-loop supply chain network with price-sensitive demand and consumer’s incentives
•Developed multi-objective optimisation model for sustainable CLSC network problem.•Considered SCs complexity, price-sensitive demand and consumer’s incentives.•Data collected from a leading European household appliance company was used.•Evidenced the positive effects of incentive pricing on returne...
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| Vydáno v: | Computers & industrial engineering Ročník 168; s. 108105 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier Ltd
01.06.2022
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| Témata: | |
| ISSN: | 0360-8352, 1879-0550 |
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| Abstract | •Developed multi-objective optimisation model for sustainable CLSC network problem.•Considered SCs complexity, price-sensitive demand and consumer’s incentives.•Data collected from a leading European household appliance company was used.•Evidenced the positive effects of incentive pricing on returned goods.•Provided multiple trade-off solutions for decision makers.
Closed-loop supply chains (CLSCs) are essential for maximising the value creation over the entire life cycle of a product. The design of these networks is increasing due to growing online businesses and rising sustainability awareness. This study develops a multi-objective optimisation model for sustainable CLSC network problem considering supply chain’s inherent complexity (multi-echelon, multi-product, multi-mode and multi-period nature) along with price-sensitive demand, consumer’s incentives and different quality levels of product. The proposed model seeks to optimise total cost and carbon emissions generated by production, distribution, transportation, and disposal activities. A two-stage algorithm, through the integration of the Non-Dominated Sorting Genetic Algorithm (NSGA-II) and Co-Kriging approach is utilised to determine the trade-off between costs and carbon emissions in the CLSC network. Data collected from a leading European household appliance company was used to analyse and interpret the developed model. The results show that the proposed two-stage approach provides robust outcomes and is computationally less expensive than the epsilon constraint approach. The study evidences the positive effects of incentive pricing on returned goods in the reverse logistics network and provides multiple trade-off solutions for supply chain managers to make informed decisions. |
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| AbstractList | •Developed multi-objective optimisation model for sustainable CLSC network problem.•Considered SCs complexity, price-sensitive demand and consumer’s incentives.•Data collected from a leading European household appliance company was used.•Evidenced the positive effects of incentive pricing on returned goods.•Provided multiple trade-off solutions for decision makers.
Closed-loop supply chains (CLSCs) are essential for maximising the value creation over the entire life cycle of a product. The design of these networks is increasing due to growing online businesses and rising sustainability awareness. This study develops a multi-objective optimisation model for sustainable CLSC network problem considering supply chain’s inherent complexity (multi-echelon, multi-product, multi-mode and multi-period nature) along with price-sensitive demand, consumer’s incentives and different quality levels of product. The proposed model seeks to optimise total cost and carbon emissions generated by production, distribution, transportation, and disposal activities. A two-stage algorithm, through the integration of the Non-Dominated Sorting Genetic Algorithm (NSGA-II) and Co-Kriging approach is utilised to determine the trade-off between costs and carbon emissions in the CLSC network. Data collected from a leading European household appliance company was used to analyse and interpret the developed model. The results show that the proposed two-stage approach provides robust outcomes and is computationally less expensive than the epsilon constraint approach. The study evidences the positive effects of incentive pricing on returned goods in the reverse logistics network and provides multiple trade-off solutions for supply chain managers to make informed decisions. |
| ArticleNumber | 108105 |
| Author | Aktas, Emel Ghadge, Abhijeet Mogale, D.G. De, Arijit |
| Author_xml | – sequence: 1 givenname: D.G. surname: Mogale fullname: Mogale, D.G. email: MogaleD@Cardiff.ac.uk organization: Logistics and Operations Management Section, Cardiff Business School, Cardiff University, Cardiff, UK – sequence: 2 givenname: Arijit surname: De fullname: De, Arijit organization: Alliance Manchester Business School, University of Manchester, Manchester, UK – sequence: 3 givenname: Abhijeet surname: Ghadge fullname: Ghadge, Abhijeet organization: Centre for Logistics and Supply Chain Management, School of Management, Cranfield University, MK43 0AL, UK – sequence: 4 givenname: Emel surname: Aktas fullname: Aktas, Emel organization: Centre for Logistics and Supply Chain Management, School of Management, Cranfield University, MK43 0AL, UK |
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| Keywords | Modelling and optimisation Multi-objective algorithm Closed-loop supply chains Sustainability Transportation |
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