Stochastic optimization of a closed-loop fashion supply chain.

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dc.contributor.authorShoarinejad, Sara
dc.contributor.examiningcommitteeMalalgoda, Narendra (Supply Chain Management)
dc.contributor.examiningcommitteeAppadoo, Srimantoorao (Supply Chain Management)
dc.contributor.supervisorTaylor, Kelsey
dc.date.accessioned2024-08-28T15:21:32Z
dc.date.available2024-08-28T15:21:32Z
dc.date.issued2024-08-22
dc.date.submitted2024-08-22T22:41:29Zen_US
dc.degree.disciplineManagement
dc.degree.levelMaster of Science (M.Sc.)
dc.description.abstractThe fashion industry, characterized by rapid changes in consumer preferences, high demand volatility, and intense global competition, faces challenges in maintaining profitability while addressing sustainability concerns. The fast-changing nature of fashion trends leads to a high turnover of products, contributing to waste and environmental degradation. These issues underscore the need for fashion companies to adopt sustainable practices and enhance their supply chain management to remain competitive and ecologically responsible. This research proposes a novel mathematical modeling approach aimed at minimizing the cost of fashion companies within a closed-loop supply chain framework, incorporating sustainability considerations, and addressing uncertainties through stochastic optimization. In the fast fashion industry, companies grapple with fluctuating consumer demands and the imperative for environmental stewardship. The perishability of fast fashion exacerbates waste, as products quickly fall out of favor, leading to environmental impacts. This thesis emphasizes the necessity of transitioning towards sustainable practices within the fashion industry, advocating for implementing closed-loop supply chains to mitigate environmental degradation while optimizing efficiency and profitability. We introduce deterministic and stochastic models tailored for the fashion industry. Our approach uses two-stage stochastic optimization to manage uncertainties in demand within the closed-loop supply chain. This model incorporates sustainability into supply chain practices, reducing environmental harm and enhancing resilience and adaptability in the face of market volatility. Furthermore, a comparative analysis of the deterministic and stochastic model results underscores the importance of accounting for demand uncertainty in optimizing fashion supply chain operations. Central to our methodology is the Sample Average Approximation (SAA) method, employed to solve the two-stage stochastic problem presented by the supply chain's dynamics. The SAA method is chosen for its robustness in handling uncertainty and its capacity to provide actionable insights based on empirical data. By applying this method, I demonstrate the feasibility of our model in real-world scenarios, guiding fashion companies toward sustainable practices without compromising profitability. This study adds to the knowledge of sustainable fashion by providing a practical solution to sector problems. Integrating sustainability and mathematical modeling opens the door to a more successful fashion business where economic goals and environmental concerns are both addressed.
dc.description.noteOctober 2024
dc.identifier.urihttp://hdl.handle.net/1993/38440
dc.language.isoeng
dc.rightsopen accessen_US
dc.subjectTwo-stage stochastic optimization
dc.subjectSample average approximation
dc.subjectFashion industry
dc.subjectSustainability
dc.subjectDemand uncertainty
dc.subjectClosed-loop supply chain management
dc.subjectCost optimization
dc.titleStochastic optimization of a closed-loop fashion supply chain.
dc.typemaster thesisen_US
local.subject.manitobano
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