Reverse Logistics Network Design under Disruption Risk for Third-Party Logistics Providers

Li, Rui; Chen, Xin

doi:10.3390/su142214936

Cited by 3 publications

(4 citation statements)

References 48 publications

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“…A review of reverse logistics definitions, trends, and new challenges are presented in [52]. Systematic literature reviews, devoted methods and criteria dedicated to assessing reverse logistics are presented in [53][54][55][56][57]. Reverse logistics in the context of remanufacturing, Industry 4.0, and closed-loop network structures are considered in [58][59][60][61][62].…”

Section: A Reverse Approach For Supporting Sustainable Product Develo...mentioning

confidence: 99%

A Data-Driven Approach for Improving Sustainable Product Development

Relich

2023

Sustainability

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A product’s impact on environmental issues in its complete life cycle is significantly determined by decisions taken during product development. Thus, it is of vital importance to integrate a sustainability perspective in methods and tools for product development. The paper aims at the development of a method based on a data-driven approach, which is dedicated to identifying opportunities for improving product sustainability at the design stage. The proposed method consists of two main parts: predictive analytics and simulations. Predictive analytics use parametric models to identify relationships within product sustainability. In turn, simulations are performed using a constraint programming technique, which enables the identification of all possible solutions (if there are any) to a constraint satisfaction problem. These solutions support R&D specialists in finding improvement opportunities for eco-design related to reducing harmful impacts on the environment in the manufacturing, product use, and post-use stages. The results indicate that constraint-satisfaction modeling is a pertinent framework for searching for admissible changes at the design stage to improve sustainable product development within the full scope of socio-ecological sustainability. The applicability of the proposed approach is verified through an illustrative example which refers to reducing the number of defective products and quantity of energy consumption.

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Section: A Reverse Approach For Supporting Sustainable Product Develo...mentioning

confidence: 99%

A Data-Driven Approach for Improving Sustainable Product Development

Relich

2023

Sustainability

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“…This study is one of the few that addresses this aspect of reverse logistics. 14 Finally, Li et al (2022) presented an advanced bi-objective mixed integer programming model that integrates distribution centers with collection and recovery centers to design a closed-loop logistics network for third-party logistics service providers. Their proposed hybrid sparse search method minimizes costs while reducing customer service time, with repairs being the only mode of recovery considered.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Their proposed hybrid sparse search method minimizes costs while reducing customer service time, with repairs being the only mode of recovery considered. 15 Despite recent efforts, few studies have addressed the integrated design of direct and reverse logistics distribution networks simultaneously, as pointed out by Ding et al (2023). 16 While some studies have made strides in this area, they have certain limitations.…”

Section: Literature Reviewmentioning

confidence: 99%

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A fuzzy mathematical model for hybrid inventory and purchase optimization in a reverse logistics system considering shortage and warehouse capacity

Tang,

Thelkar

2023

Science Progress

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Making decisions about the design and implementation of a logistics network is crucial as it has long-term impacts. However, it is important to consider that demand factors and the number of returned items by customers may change over time. Therefore, it is necessary to design a logistics network that can adapt to various demand fluctuations. The main goal of this study is to calculate the quantity of products that should be sent at different times in a supply chain network to minimize the overall cost of reverse logistics and tardiness time. Accordingly, a multi-objective mathematical model is proposed that aims to optimize the total cost and the amount of delay in sending customer orders in a three-level logistics network, assuming that some parameters are uncertain. Additionally, the minimization of waiting time, considering the level of delay in sending, is applied as the second objective function. To handle the uncertainty in the reverse logistics network, a fuzzy approach is implemented, and the proposed model is solved using GAMS software. Furthermore, to solve the mathematical model in large dimensions, the Cuckoo Optimization Algorithm (COA) is applied in MATLAB software, and the results are compared to the global optimal solution. The outcomes show that the proposed algorithm has a desirable performance, as the total values sent to the manufacturer are equal to those obtained from the exact solution, and the objective function value decreases as the number of repetitions increases.

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Green supply chain management, risk-taking, and corporate value—Dual regulation effect based on technological innovation capability and supply chain concentration

Zhang

Dou

Wang

2023

Front. Environ. Sci.

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With the promotion of carbon-peak and carbon-neutral strategies and the increase in green awareness, green development is gradually gaining attention, and the green supply chain management (GSCM) derived from traditional supply chain management is gradually becoming a path to promote green development. At the same time, enterprise, as an important source of pollution, how to consider social responsibility, such as environmental protection, in the process of ensuring efficiency improvement has become an important issue. To study the impact of green supply chain management on enterprise value and its path of action, this paper examines the impact of green supply chain management on enterprise value, explores the moderating effect of the risk-taking level, and further analyzes the dual moderating effect played by technological innovation capability and supply chain concentration. Based on the micro data of 131 Chinese listed enterprises from 2014 to 2021, a panel-regression model is used to illustrate how green supply chain management affects enterprise value, and the results show that: 1) green supply chain management can promote enterprise value; 2) the level of risk-taking strengthens the promoting effect of green supply chain management on enterprise value enhancement; and 3) the technological innovation capability negatively regulates the moderating effect of risk-taking, while the supply chain concentration positively regulates the moderating effect of risk-taking. The research results of this paper enrich the path of the effect of implementing of green supply chain management on enterprise value enhancement, i.e., the process of green supply chain management to enhance enterprise value is regulated by the level of enterprise risk-taking, while technological innovation capability and supply chain concentration will also regulate the level of enterprise risk-taking and thus promote enterprise value enhancement. This research not only extends the research perspective and enriches the existing research, but also provides a theoretical basis for enterprises to implement green supply chain management to promote value enhancement and improve the level of green supply chain management implementation and the green development of enterprises.

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Reverse Logistics Network Design under Disruption Risk for Third-Party Logistics Providers

Cited by 3 publications

References 48 publications

A Data-Driven Approach for Improving Sustainable Product Development

A Data-Driven Approach for Improving Sustainable Product Development

A fuzzy mathematical model for hybrid inventory and purchase optimization in a reverse logistics system considering shortage and warehouse capacity

Green supply chain management, risk-taking, and corporate value—Dual regulation effect based on technological innovation capability and supply chain concentration

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