A Novel Closed-Loop Supply Chain Network Design Considering Enterprise Profit and Service Level

Abstract

Increasing concerns for sustainable development have motivated the study of closed-loop supply chain network design from a multidimensional perspective. To cope with such issues, this paper presents a general closed-loop supply chain network comprising various recovery options and further formulates a multi-objective mixed-integer linear programming model considering enterprise profit and service level simultaneously. Within this model, market segmentation is also considered to meet real-world operating conditions. Moreover, an ε -constraint method and two interactive fuzzy approaches are applied to find a global optimum for this model together with the decisions on the numbers, locations, and capacities of the facilities, as well as the material flow through the network. Ultimately, numerical experiments are conducted to demonstrate the viability and effectiveness of both the proposed model and solution approaches.

Efficient Allocation of Customers to Facilities in the Multi-Objective Sustainable Location Problem

“…In classical methods, a MOO problem would be converted into a single objective formulation using the weighted sum or the ε-constraint approach, for example. This can be found in several studies [20,[25][26][27]. The main advantage of classical methods is to model and solve the multi-objective problem with single-objective approaches.…”

Designing a Sustainable Reverse Logistics Network Considering the Conditional Value at Risk and Uncertainty of Demand under Different Quality and Market Scenarios

“…Recently, environmental factors and commercial factors such as commitment have led to the consideration of risk in reverse logistics networks [20,21]. Therefore, supply chain risks should be recognized in order for them to be managed [22,23].…”

Fuzzy Bi-Objective Closed-Loop Supply Chain Network Design Problem with Multiple Recovery Options

“…First, there has been extensive research into the concept and solution methods laying the foundation of the CLSC network and focusing on the network hierarchy, facilities classification, processing methods, optimization methods and so forth (e.g., [1,2]). Second, research has explored the design of a multi-objective CLSC network taking into account its economic, efficient and sustainable effects, most of which has aimed to build an economical, environmentally friendly and efficient supply chain (e.g., [3,4]). Third, the design of the CLSC network under uncertain environments considering the high complexity, supply-demand imbalance, and other indeterministic factors in the structure has been explored to simulate real environments (e.g., [5,6]).…”

“…Pourjavad et al [9] minimized the total cost and lowered the environmental impact simultaneously. Jiang et al [3] advanced a CLSC network considering enterprise profit and service level simultaneously.…”

“…(2) establishing a fuzzy bi-objective MILP model which maximizes both company profit and customer satisfaction level for the CLSC network design under fuzzy environments; (3) presenting a two-stage fuzzy interactive solution framework to solve the formulated fuzzy optimization model by integrating the fuzzy expected value operator, fuzzy ranking method and fuzzy interactive solution method; (4) comparing the performance of the fuzzy CLSC model with the deterministic one in [3] by several numerical experiments to demonstrate the importance and necessity of designing the CLSC network under fuzzy environments.…”