isk Management of Transportation Routes Considering Equivalence Relationships in the Sustainable Supply Chain of Perishable Goods

نوع: Type: thesis

مقطع: Segment: masters

عنوان: Title: isk Management of Transportation Routes Considering Equivalence Relationships in the Sustainable Supply Chain of Perishable Goods

ارائه دهنده: Provider: shiva momeni

اساتید راهنما: Supervisors: Dr.Javad behnamian

اساتید مشاور: Advisory Professors:

اساتید ممتحن یا داور: Examining professors or referees: Dr.Vahid khodakarami,DR.Nafise soleimani

زمان و تاریخ ارائه: Time and date of presentation: 2024

مکان ارائه: Place of presentation: ۶۲

چکیده: Abstract: Abstract: With the increasing demand for perishable products and the multiple challenges in managing the supply chain for these goods, there is a heightened need for a comprehensive and optimized model that not only meets economic and environmental requirements but also minimizes delays and waste. Inefficiencies in the perishable product supply chain, due to time constraints and preservation sensitivities, can lead to increased waste, additional costs, and reduced service quality. This research aims to provide a solution that optimally manages the supply chain, reducing costs while ensuring sustainability and product quality. The main problem addressed in this study is the sustainable and optimal management of the perishable product supply chain, considering transportation and storage costs as well as environmental impacts. Given the time constraints and specific conditions required to maintain product quality, delivery delays can lead to increased waste and decreased customer satisfaction. The objective of this research is to propose a model that, considering all economic, environmental, and social dimensions, optimizes costs and delivery times while preserving product quality. To solve this problem, a multi-objective, multi-period model for the perishable product supply chain has been developed. Through linear programming and mathematical modeling, the proposed model identifies optimal routes, adjusts vehicle capacities, and selects optimal delivery times and conditions, while providing alternative routes in critical situations. This model aims to reduce overall supply chain costs and enhance sustainability by integrating economic, environmental, and social considerations. The designed model, given its inclusion of various dimensions of the supply chain and risk management of routes, is characterized by significant computational complexities, setting it apart from traditional models. These complexities include managing large datasets, the need for rapid processing, and the simultaneous analysis of multiple objectives, all of which must be addressed concurrently under various conditions. Therefore, to solve the problem and find optimal solutions, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) was employed. This algorithm, with its capability for multi-objective optimization, has brought meaningful improvements to the model’s outcomes. Finally, the results from implementing the model indicate that the proposed approach outperforms traditional methods and competing algorithms by reducing supply chain costs, enhancing environmental sustainability, and significantly decreasing perishable product waste. Moreover, the findings demonstrate that the use of NSGA-II in this research has provided more efficient optimization compared to other methods, increasing customer satisfaction through quality preservation and reduced delivery times.

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