Optimization-based model of a circular supply chain for coffee waste

Hanieh Zohourfazeli , Ali Sabaghpourfard , Amin Chaabane , Armin Jabbarzadeh
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Abstract

Spent coffee grounds (SCG) waste poses significant environmental challenges, including greenhouse gas emissions and contamination risks. However, the existing reverse logistics (RL) systems remain inefficient, costly, and prone to contamination. Although previous studies have explored RL strategies, economically viable logistics models for small-scale SCG operations remain underdeveloped. However, the role of digitalization in optimizing SCG collection has not yet been explored. This study addresses these gaps by developing and evaluating sustainable business models that integrate circular economy principles with Industry 4.0. A mixed-integer linear programming (MILP) model was formulated to optimize the location, allocation, and routing decisions for “circular coffee shops, ” which serve as local collection and preprocessing nodes. Using real data from 1000 coffee shops in Montreal, three case scenarios were analyzed to assess the impact of pre-drying technologies and smart logistics on cost reduction and environmental performance. The results show that, while smart bins and real-time data analytics improve network efficiency and sustainability, the strategic placement of pre-drying technologies significantly reduces transportation and processing costs. By introducing a novel framework that integrates digitalization and collaborative waste management, this study advances SCG valorization and minimizes waste-related environmental impact. The findings offer actionable strategies for municipalities and food service stakeholders, providing a scalable, data-driven approach to promote the adoption of circular economy principles in urban organic waste management.
基于优化的咖啡废弃物循环供应链模型
废弃咖啡渣(SCG)废弃物对环境构成了重大挑战,包括温室气体排放和污染风险。然而,现有的逆向物流(RL)系统仍然效率低下,成本高,容易污染。虽然以前的研究已经探索了RL策略,但小规模SCG作业的经济可行的物流模型仍然不发达。然而,数字化在优化SCG收集中的作用尚未得到探索。本研究通过开发和评估将循环经济原则与工业4.0相结合的可持续商业模式来解决这些差距。制定了混合整数线性规划(MILP)模型来优化“圆形咖啡店”的位置、分配和路由决策,作为本地收集和预处理节点。利用蒙特利尔1000家咖啡店的真实数据,分析了三种情况,以评估预干燥技术和智能物流对降低成本和环境绩效的影响。结果表明,虽然智能垃圾箱和实时数据分析提高了网络效率和可持续性,但预干燥技术的战略性部署显著降低了运输和加工成本。通过引入一个集成数字化和协同废物管理的新框架,本研究推进了SCG的增值,并最大限度地减少了与废物相关的环境影响。研究结果为市政当局和食品服务利益相关者提供了可行的战略,提供了一种可扩展的、数据驱动的方法,以促进在城市有机废物管理中采用循环经济原则。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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