Closed-loop supply chain network design under demand, return and quality uncertainty

Biçe, Kadir; Batun, Sakine

doi:10.1016/j.cie.2020.107081

Cited by 30 publications

(13 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Strategic and operational backup decisions were developed to increase the resiliency of the system against disruption of the facilities and routes simultaneously. Biçe and Batun [19], considered the problem of designing a CLSC network including the uncertainty in demand quantities, return rates, and quality of returned products. They designed the problem as a two-stage stochastic mixed-integer program to maximize the profit of the system.…”

Section: Literature Surveymentioning

confidence: 99%

An agent-based modeling framework for the design of a dynamic closed-loop supply chain network

Bozdoğan

Aykut

Demirel

2022

Complex Intell. Syst.

View full text Add to dashboard Cite

The supply chain is a dynamic and uncertain system consisting of material, information, and fund flows between different organizations, from the acquisition of the raw materials to the delivery of the finished products to the end customers. Closed-loop supply chains do not end with the delivery of the finished products to the end customers, the process continues until economic value is obtained from the returned products or they are disposed properly in landfills. Incorporating reverse flows in supply chains increases the uncertainty and complexity, as well as complicating the management of supply chains that are already composed of different actors and have a dynamic structure. Since agent-based modeling and simulation is a more efficient method of handling the dynamic and complex nature of supply chains than the traditional analytical methods, in this study agent-based modeling methodology has been used to model a generic closed-loop supply chain network design problem with the aims of integrating customer behavior into the network, coping with the dynamism, and obtaining a more realistic structure by eliminating the required assumptions for solving the model with analytical methods. The actors in the CLSC network have been defined as agents with goals, properties and behaviors. In the proposed model dynamic customer arrivals, the changing aspects of customers' purchasing preferences for new and refurbished products and the time, quantity and quality uncertainties of returns have been handled via the proposed agent-based architecture. To observe the behavior of the supply chain in several conditions various scenarios have been developed according to different parameter settings for the supplier capacities, the rate of customers being affected by advertising, the market incentive threshold values, and the environmental awareness of customers. From the scenarios, it has been concluded that the system should be fed in the right amounts for the new and refurbished products to increase the effectiveness of factors such as advertising, incentives, and environmental awareness for achieving the desired sales amounts and cost targets.

show abstract

Section: Literature Surveymentioning

confidence: 99%

An agent-based modeling framework for the design of a dynamic closed-loop supply chain network

Bozdoğan

Aykut

Demirel

2022

Complex Intell. Syst.

View full text Add to dashboard Cite

show abstract

“…Duan et al [33] considered the impact of consumers' preference and AI-Push on the CLSC network equilibrium. Biçe and Batun [34] studied the CLSC network equilibrium considering the qualities of the returned products. Pourmehdi et al [35] studied the equilibrium decision-making of a steel CLSC network involving production technology.…”

Section: Equilibrium In a Competitive Clsc Networkmentioning

confidence: 99%

“…Fu et al [37] proposed a CLSC network model dealing with heterogeneous products facing different market demands. Existing research work [23][24][25][26][27][28][29][30][31][32][33][34][35][36][37] not only obtained CLSC network equilibrium decision-making but also analyzed how external factors, such as random demand, manufacturing level, production period, carbon emission, etc., can affect the equilibrium decision-making. However, all these research works only considered the OEMs' self-remanufacturing policy but did not consider their outsourcing remanufacturing policy.…”

Section: Equilibrium In a Competitive Clsc Networkmentioning

confidence: 99%

“…The reverse flows of CLSC involve used products, which are returned from the demand markets to the original manufacturers or the remanufacturers for recycling. However, existing research on the CLSC network equilibrium problem [22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37] have not considered the manufacturers' options of remanufacturing their products or outsourcing their products to other manufacturers for remanufacturing. Moreover, the actual production and operation of manufacturing companies may also need to consider thirdparty remanufacturing.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Remanufacturing Policies Options for a Closed-Loop Supply Chain Network

2021

View full text Add to dashboard Cite

Due to the need for resource utilization and environmental protection, remanufacturing is used as an effective means to achieve a circular economy. To focus on the production and sales of new products, manufacturers outsource the remanufacturing of used products to remanufacturers. Aiming at helping manufacturers to choose between self-remanufacturing and outsourcing remanufacturing policies, a closed-loop supply chain network equilibrium model considering the remanufacturing policy options is established. The equilibrium decision-making is obtained by using the variational inequality method. Furthermore, the criteria for manufacturers to choose between the two remanufacturing policies based on different factors such as recovery rates of the used products, remanufacturing costs, and environmental impact parameters, are given. Numerical examples show the following results: (1) When compared with self-remanufacturing policy, outsourcing remanufacturing policy can save resources, increase the sales of products, and have a smaller environmental impact. (2) When the recycling rate of used products is low, choosing an outsourcing remanufacturing policy can increase the sales of products. When the recycling rate is high, choosing a self-remanufacturing policy can get more profits. (3) When the costs of a self-remanufacturing policy and an outsource-remanufacturing policy are quite different, choosing the outsourcing remanufacturing policy can save resources and protect the environment.

show abstract

“…Regular forward supply chains include the forward flow of products through suppliers, plants, and distributors to customers. RL consists of the reverse flow of products starting from end customers and involves collecting, inspecting, repairing, disassembly, disposal, recycling, and remanufacturing of products [2], [3]. Even during and after a critical circumstance (like pandemic COVID-19), it is essential to activate the openedand closed-loop system through an efficient and resilient supply chain network [4].…”

Section: Introductionmentioning

confidence: 99%

A novel algorithm to allocate customers and retailers in a closed-loop supply chain under probabilistic demand

Keramatlou¹,

Javadian²,

Didehkhani³

et al. 2022

Preprint

View full text Add to dashboard Cite

In this paper, a closed-loop supply chain (CLSC) is modeled to obtain the best location of retailers and allocate them to other utilities. The structure of CLSC includes production centers, retailers’ centers, probabilistic customers, collection, and disposal centers. In this research, two strategies are considered to find the best location for retailers by focusing on 1- the type of expected movement 2- expected coverage (distance and time) for minimizing the costs and maximizing the profit by considering the probabilistic customer and uncertainly demand. First of all, the expected distances between customers and retailers are calculated per movement method. These values are compared with the Maximum expected coverage distance of retailers, which is displayed in algorithm 1 heuristically, and the minimum value is picked. Also, to allocate customers to retailers, considering the customer's movement methods and comparing it with Maximum expected coverage time, which is presented in Algorithm 2 heuristically, the minimum value is chosen to this end, a bi-objective nonlinear programming model is proposed. This model concurrently compares Strategies 1 and 2 to select the best competitor. Based on the chosen strategy, the best allocation is determined by employing two heuristic algorithms, and the locations of the best retailers are determined. As the proposed model is NP-hard, a meta-heuristics (non-dominated sorting genetic) algorithm is employed for the solution process. Afterward, the effectiveness of the proposed model is validated and confirmed, and the obtained results are analyzed. For this purpose, a numerical example is given and solved through the optimization software.

show abstract

Closed-loop supply chain network design under demand, return and quality uncertainty

Cited by 30 publications

References 43 publications

An agent-based modeling framework for the design of a dynamic closed-loop supply chain network

An agent-based modeling framework for the design of a dynamic closed-loop supply chain network

Remanufacturing Policies Options for a Closed-Loop Supply Chain Network

A novel algorithm to allocate customers and retailers in a closed-loop supply chain under probabilistic demand

Contact Info

Product

Resources

About