4.6 Article

Minimization of the Environmental Emissions of Closed-Loop Supply Chains: A Case Study of Returnable Transport Assets Management

期刊

SUSTAINABILITY
卷 10, 期 2, 页码 -

出版社

MDPI
DOI: 10.3390/su10020329

关键词

closed-loop supply chain (CLSC); returnable transport items (RTIs); environmental impact; sustainability; simulation; multi-objective optimization; case study

资金

  1. Italian Ministry of University and Research under the SIR (Scientific Independence of young Researchers)
  2. [D92115000210008]
  3. [RBSI14L97M]

向作者/读者索取更多资源

This study investigates the issue of minimizing the environmental burden of a real closed-loop supply chain (CLSC), consisting of a pallet provider, a manufacturer and several retailers. A simulation model is developed under Microsoft ExcelTM (Microsoft Corporation, Washington, US) to reproduce the flow of returnable transport items (RTIs) in the CLSC and to compute the corresponding environmental impact. Multi-objective optimization, including some relevant environmental key performance indicators (KPIs), is then carried out exploiting the commercial software ModeFRONTIERTM (ESTECO S.p.A., Trieste, Italy), to determine the settings that minimize emissions of the CLSC. In addition, economic and strategic metrics are taken into account in the optimization, to make the analysis more comprehensive. Three scenarios are considered (one base scenario and two scenarios examined in a sensitivity analysis) with different relative importance assigned to the metrics subject to optimization. Results show that the asset retrieving operations contribute to the environmental impact of the system to the greatest extent, mainly because of the quite relevant distance between Company A and its customers. Conversely, emissions due to the purchase of new assets contribute to the total environmental impact of the system to a very limited extent. Because the analysis is grounded on a real CLSC, the results are expected to provide practical indications to logistics and supply chain managers, to minimize the environmental performance of the system.

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