Hybrid simulation modeling for regional food systems
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In response to concerns regarding the serious environmental and social issues associated with conventional food distribution systems, consumer demand for regionally-produced food is growing. Regional food hubs are playing a critical role in meeting this growing demand. Food hubs aggregate, distribute, and market regionally-produced food, with a goal of promoting and supporting environmental and social sustainability. They provide an alternative distribution channel through which small and mid-sized producers can access wholesale markets, and they improve consumer access to regional food at competitive prices. Despite the benefits they provide, food hubs struggle to maintain profitability, and they face many challenges to growth and success. In particular, they are often unable to achieve the logistical and operational efficiencies that characterize conventional large-scale food distribution. This is partly due to a lack of implementation of efficiency-enhancing conventional supply chain practices in food hub operations. One possible method of improving food hub efficiency targets their inbound logistics operations. This thesis studies the inbound operations of a regional food hub in Iowa, with a focus on the scheduling of producers’ deliveries to the food hub.
This thesis proposes a hybrid simulation modeling framework to show how the advantages of both discrete event simulation (DES) and agent-based simulation (ABS) can be leveraged to address socio-technical problems in regional food supply chains. The usefulness of this hybrid methodology is demonstrated through the development of an empirically-based hybrid simulation model of the inbound logistics operations of a food hub in Iowa. ABS was used to model the decision-making process of producers for scheduling their deliveries. DES was used to model the inbound operations of the food hub, including the receiving and storing of the goods brought by the producers. Four different versions of the hybrid simulation model are used to examine the effectiveness of various policies in encouraging producers to schedule their deliveries, as well as the impacts of producer scheduling on food hub efficiency and effectiveness. Experimental results suggest that different incentives vary in their degree of effectiveness, and increasing the percentage of producers who schedule their deliveries is unlikely to improve overall system operations by itself – in order for all participants to benefit, the food hub manager must also adjust the hub’s inbound operations to account for producers who refuse to schedule. This hybrid model will help guide policy recommendations to food hub managers to make their inbound operations more efficient and effective.