Multi-objective optimization of agro-food supply chain networking problem integrating economic viability and environmental sustainability through type-2 fuzzy-based decision making

Abstract

Balancing economic and environmental considerations in Agro-Food Supply Chain Networks (AFSCNs) is a critical challenge faced by decision-makers in developing countries. This study focuses on the Apple industry’s supply chain network problem and emphasizes the importance of environmentally friendly transportation systems. To address this concern, a multi-objective mixed-integer transportation model is developed to maximize profit by considering revenue and rewards for lower CO2 emissions while simultaneously minimizing costs associated with purchase, loading, unloading, transportation, fixed expenses, CO2 taxes, and penalties for exceeding permitted emission levels and reducing overall carbon dioxide (CO2) emissions in the AFSCN. Uncertain parameters, including revenue, purchase cost, loading cost, unloading cost, reward, fuel consumption, and CO2 emissions for different fuel-type vehicles, are handled using type-2 picture fuzzy numbers for accounting for uncertainty. The data and information used in this study were acquired from a survey conducted among Apple industry wholesalers in Shimla, Mandi, and Kothkai in Himachal Pradesh, providing authentic and reliable insights on supply chain network dynamics. The proposed multi-objective model is solved using LINGO 19.0 optimization software, utilizing diverse optimization methodologies, including the weighted sum method, fuzzy goal programming, interactive fuzzy satisfying technique, global criteria methodology, and weighted Tchebycheff metrics programming. This enables decision-makers to make informed choices and optimize the AFSCN’s problems on economic and environmental performance. Additionally, sensitivity analysis is conducted to evaluate the model’s resilience and responsiveness to changes in the carbon budget, carbon cap, and CO2 emission sources. The results demonstrate the model’s suitability for assessing different scenarios and policy measures, providing insights into the potential impact on the AFSCN’s economic viability and environmental sustainability.