Designing a multi-objective closed-loop supply chain: a two-stage stochastic programming, method applied to the garment industry in Montréal, Canada

Abstract

The global population continues to grow, which expands demand for raw materials. Meanwhile, governments are developing circular economy strategies within cities and their industries. A circular economy utilizes refurbishing, reusing, remanufacturing, and repairing of products and materials. For companies, this involves to set targets and to rethink their supply chain. This paper seeks to model an exhaustive multi-echelon closed-loop supply chain (CLSC) network. This network functions within uncertainty, and the model optimizes three different objectives. The first objective function maximizes the network's profit; the second objective function minimizes network emissions. The last objective function maximizes job positions created by the network. Optimizing three contradicting objectives is a problem, so an augmented epsilon constraint method is applied to improve the model. Given the rise of fast fashion in developed countries, this model is used in the clothing industry in Montreal, Canada. The model includes three scenarios over five years with two types of products. The result shows the attractiveness of such a network for companies looking for profit, sustainability, and entrepreneurship in the garment industry.

A fuzzy multiobjective linear programming approach for green multiechelon distribution network design

“…There are two types of approaches to handling uncertainty. Fuzzy programming is a mathematical model that deals with static uncertainty and can be reformulated as a crisp model (Liang, 2006; Paksoy et al , 2012; Dey et al , 2015; Gholamian et al , 2015), while stochastic programming (Amin and Zhang, 2013; Elfarouk et al , 2022; Shafiee Roudbari et al , 2023) handles dynamic uncertainty and uses scenario-based objectives and constraints to solve the problem. Amin and Zhang (2013) used stochastic programming, ε -constraint and weighted sums methods to solve a multiobjective facility location problem by minimizing the total cost and maximizing the usage of environmentally friendly materials and clean technologies under uncertain demand and customer return.…”

“…total cost, carbon emission and social impacts. Shafiee Roudbari et al (2023) offered a multiobjective stochastic programming model for a garment closed-loop supply chain network design problem, in which total profit, emissions and job creation are optimized simultaneously.…”

“…In terms of decisions, Esmaeilian et al (2023) and Duffuaa and Mohammed (2023) do not include capacity decision in their study. For studies, such as that of Amin and Zhang (2013), Mohammed and Wang (2017), Jindal and Sangwan (2017), Boronoos et al (2021), Boskabadi et al (2022) and Shafiee Roudbari et al (2023), the uncertainties in model parameters are captured. Nevertheless, Amin and Zhang (2013), Jindal and Sangwan (2017), Mohammed and Wang (2017) and Shafiee Roudbari et al (2023) do not include the impact from different transportation modes.…”

“…For studies, such as that of Amin and Zhang (2013), Mohammed and Wang (2017), Jindal and Sangwan (2017), Boronoos et al (2021), Boskabadi et al (2022) and Shafiee Roudbari et al (2023), the uncertainties in model parameters are captured. Nevertheless, Amin and Zhang (2013), Jindal and Sangwan (2017), Mohammed and Wang (2017) and Shafiee Roudbari et al (2023) do not include the impact from different transportation modes. The most relevant studies to our research are those of Boronoos et al (2021) and Boskabadi et al (2022).…”