Fuzzy multiple-objective linear programming model for transportation mode and storage mode selection in fruit value chain: a case study of mangosteen

This independent study presents a Fuzzy Multiple-Objective Linear Programming (FMOLP) model designed to optimize the selection of transportation and storage modes within the mangosteen value chain. The objective is to determine the optimal flows of the mangosteen value chain by considering both ambient and cold mode selection in storage and transportation, as well as various factors such as transportation and storage loss, cost management, and carbon emissions in uncertain situations. This study evaluates various optimization methods, including Linear Programming, Fuzzy Linear Programming (Weighted Average Method and Maximize Minimum Satisfaction Method), and Fuzzy Multi-Objective Linear Programming (Maximize Weighted Average satisfaction method and Maximize Minimum satisfaction method). By comparing these methods, the study identifies the optimal strategies for minimizing spoilage, reducing costs, and lowering carbon emissions while maintaining product quality and customer satisfaction. The findings suggest that while the fuzzy weighted average method offers the highest and most stable profits, the fuzzy multi-objective linear programming (maximize weighted average satisfaction method) provides a balanced approach that significantly reduces carbon emissions without compromising profitability. This study also aims to determine a compromise solution between total profit and total carbon emissions of the mangosteen value chain. This comprehensive approach provides valuable managerial insights, making it a viable option for businesses prioritizing environmental impact and operational efficiency.