Reverse logistics of empty pesticide containers: solution or a problem?

Customers’ pressure, social responsibility, and government regulations have motivated the enterprises to consider the reverse logistics (RL) in their operations. Recently, companies frequently outsource their RL practices to third-party reverse logistics providers (3PRLPs) to concentrate on their primary concern and diminish costs. However, to select the suitable 3PRLP candidate requires a multi-criteria decision making (MCDM) process involving uncertainty owing to the presence of many associated aspects. In order to choose the most appropriate sustainable 3PRLP (S3PRLP), we introduce a hybrid approach based on the classical Combined Compromise Solution (CoCoSo) method and propose a discrimination measure within the context of hesitant fuzzy sets (HFSs). This approach offers a new process based on the discrimination measure for evaluating the criteria weights. The efficiency and practicability of the present approach are numerically demonstrated by solving an illustrative case study of S3PRLPs selection under a hesitant fuzzy environment. Moreover, sensitivity and comparative studies are presented to highlight the robustness and strength of the introduced methodology. The result of this work concludes that the introduced methodology can recommend a more feasible performance when facing with determinate and inconsistent knowledge and qualitative data.

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Robust network design for sustainable-resilient reverse logistics network using big data: A case study of end-of-life vehicles

Transportation Research Part E Logistics and Transportation Review ◽

10.1016/j.tre.2021.102279 ◽

2021 ◽

Vol 149 ◽

pp. 102279

Author(s):

Kannan Govindan ◽

Hadi Gholizadeh

Keyword(s):

Big Data ◽

Network Design ◽

End Of Life ◽

Reverse Logistics ◽

Logistics Network ◽

Robust Network Design ◽

Reverse Logistics Network ◽

Robust Network

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A system dynamics model for routing and scheduling of cross-dock and transportation in reverse logistics network of perishable goods

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-200610 ◽

2021 ◽

pp. 1-17

Author(s):

Pezhman Abbasi Tavallali ◽

Mohammad Reza Feylizadeh ◽

Atefeh Amindoust

Keyword(s):

System Dynamics ◽

Reverse Logistics ◽

Logistics Network ◽

Routing And Scheduling ◽

Perishable Goods ◽

Decision Variables ◽

Proposed Model ◽

Reverse Logistics Network ◽

The Cross ◽

Space Requirements

Cross-dock is defined as the practice of unloading goods from incoming vehicles and loading them directly into outbound vehicles. Cross-docking can simplify supply chains and help them to deliver goods to the market more swiftly and efficiently by removing or minimizing warehousing costs, space requirements, and use of inventory. Regarding the lifetime of perishable goods, their routing and scheduling in the cross-dock and transportation are of great importance. This study aims to analyze the scheduling and routing of cross-dock and transportation by System Dynamics (SD) modeling to design a reverse logistics network for the perishable goods. For this purpose, the relations between the selected variables are first specified, followed by assessing and examining the proposed model. Finally, four scenarios are developed to determine the optimal values of decision variables. The results indicate the most influencing factors on reaching the optimal status is the minimum distance between the cross-dock and destination, rather than increasing the number of manufactories.

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