As the largest university in North Texas and second largest in The University of Texas System, UTA is located in the heart of Dallas-Fort Worth, challenging our students to engage with the world around them in ways that make a measurable impact.
Regional Food Transportation for Texas Farmers
Sources of Funding: Southern Sustainable Agriculture Research and Education (S-SARE) Program
This project seeks to investigate the transportation challenges faced by Texas farmers and ranchers and to design, develop, and pilot a transportation management tool that will help these farmers begin to build efficient, collaborative regional food transportation networks. Regional food systems offer the potential to greatly improve agricultural sustainability. However, in the face of increasing competition, regional farmers must find ways of expanding their market reach to a larger number of buyers to ensure the survival of their farms. Larger markets are typically located in urban centers that are geographically distant from farmers, and most small and mid-sized farmers do not have the necessary transportation infrastructure in place to support efficient distribution. If successful, this project will strengthen the Texas regional food system by increasing the market reach of farmers, thereby increasing farm incomes and long-term financial resilience.
Application
This project will follow a systems engineering approach, in which we will elicit the transportation requirements of a broad and inclusive set of regional food system stakeholders and then translate these requirements into the design and development of a transportation management tool (i.e., an app). This tool will facilitate connections between farmers and transportation providers to increase the capabilities of the Texas regional food distribution system. We define this system broadly, to include large-scale food logistics providers, small-scale transportation, and non-traditional partners, allowing for the flexibility and creativity that are necessary when working with a budget-constrained supply network with participants that are widely dispersed across a very large geographic region.
Modeling
One potential solution is collaborative transportation, in which farmers who need transportation can pay other farmers to pick up and deliver their products for them. However, collaborative transportation is challenging to coordinate. Farmers could benefit from a tool that connects them with collaborative partners and helps them to estimate and allocate transportation costs fairly. Agent-based modeling has been used to test the impact of different transportation service pricing strategies on the success of a decentralized digital mediation platform for regional food system transportation collaboration. The model is demonstrated for a set of 21 farmers who are located northeast of Dallas, Texas, and are transporting their products to a common aggregator. Preliminary experiments suggest that the ability of an online platform to facilitate transportation collaboration among farmers may be hindered by large transportation distances between the farmers, as well as the small size of the pool of potential collaborators.
Papers
- Marusak, A., Sadeghiamirshahidi, N., Krejci, C. C., Mittal, A., Beckwith, S., Cantu, J., Morris, M., & Grimm, J. (2021). “Resilient regional food supply chains and rethinking the way forward: Key takeaways from the COVID-19 pandemic”, Agricultural Systems, Vol. 190, No. 103101. doi: 10.1016/j.agsy.2021.103101
An agent-based model of digitally-mediated farmer transportation collaboration
Collaborative Food Supply Chains for Iowa’s Farmers
Sources of Funding: North Central Region Sustainable Agriculture Research and Education (NCR-SARE) Program
As the largest university in North Texas and second largest in The University of Texas System, UTA is located in the heart of Dallas-Fort Worth, challenging our students to engage with the world around them in ways that make a measurable impact. As the largest university in North Texas and second largest in The University of Texas System, UTA is located in the heart of Dallas-Fort Worth, challenging our students to engage with the world around them in ways that make a measurable impact. As the largest university in North Texas and second largest in The University of Texas System, UTA is located in the heart of Dallas-Fort Worth, challenging our students to engage with the world around them in ways that make a measurable impact.
Application
As the largest university in North Texas and second largest in The University of Texas System, UTA is located in the heart of Dallas-Fort Worth, challenging our students to engage with the world around them in ways that make a measurable impact.
Modeling
As the largest university in North Texas and second largest in The University of Texas System, UTA is located in the heart of Dallas-Fort Worth, challenging our students to engage with the world around them in ways that make a measurable impact.
Papers
- Mittal, A., Krejci, C.C., & Craven, T.J. (2018), “Logistics Best Practices for Regional Food Systems: A Review”, Sustainability, Vol. 10, No. 168.
- Mittal, A., White, V.M., & Krejci, C.C. (2017), “A Framework for Collaboration among Regional Food System Participants”, Proceedings of the Industrial & Systems Engineering Research Conference, Pittsburgh, PA, May 20-23.
Crowd Logistics for Regionalized Food Distribution
Sources of Funding: National Science Foundation
Crowd logistics is a term that describes crowdsourced transport and delivery of goods and freight. Senders source cost-effective logistics services from individual carriers via an online platform, which is controlled by a digital management system. To be successful, a platform must rapidly scale up its sender and carrier networks. If there are too few participants, senders and recipients will be dissatisfied by unfilled service requests, carriers will have insufficient opportunities, and the initiative will fail. This award supports a fundamental understanding of crowd logistics platform design for robust network growth and performance by attracting and retaining participants having a variety of economic and social motivations.
Application
The knowledge gained from this research will facilitate the use of crowd logistics for resilient food distribution in the face of large-scale disruptions, such as the COVID-19 emergency. The educational plan seeks to implement participatory modeling activities that will improve STEM students’ capacity for systems thinking, which is critical in the design and analysis of complex logistics systems.
Modeling
This research will produce a novel agent-based modeling approach to systematically explore the impacts of a crowd logistics platform’s design on its ability to quickly achieve a critical mass of participants. This approach will model the degree of control that a platform management system assumes over participants’ digital exchanges. At one end of the spectrum is a platform characterized by centralized control, full automation, and algorithmic management; at the other end is a platform with decentralized control and community-driven exchanges. Existing research on crowdsourcing platform design suggests that the degree of centralization of control impacts platform growth over time. However, understanding and predicting network effects that will lead to long-term platform growth is challenging, because the feedback loop perpetuated by participant decisions and interactions yields complex and dynamic system behavior. This research will address this challenge by representing carriers and senders as autonomous, heterogeneous, and adaptive agents, whose decisions to participate in a crowd logistics platform impact the participation of other agents over time. Participatory modeling sessions with crowd logistics practitioners will be leveraged for model validation, to ensure that agent behaviors correspond to those of their real-world counterparts.
Regional Food Hubs
Sources of Funding: Leopold Center for Sustainable Agriculture
A food hub is an organization that facilitates the distribution of primarily locally grown, source-identified food from farmers to customers. The definition of food hub is not strict; a membership-based food co-op could qualify as a food hub, as could a community-supported agriculture (CSA) initiative that brings boxes of food to a central site for distribution. The key feature of a food hub, however, is typically that it offers more supply chain management than direct-to-consumer market channels like farmers markets, to offer higher volume to customers such as restaurants or local-focused grocery stores as well as to consumers. Although food hubs have demonstrated numerous community benefits, such as increasing access to healthy food and supporting rural workforce development, they face endemic challenges in balancing supply and demand, resistance to paying a premium price for local, fresher products; and managing growth if they are successful.
Application
As the largest university in North Texas and second largest in The University of Texas System, UTA is located in the heart of Dallas-Fort Worth, challenging our students to engage with the world around them in ways that make a measurable impact.
Modeling
Based on qualitative and quantitative data gathered from 22 customers and 11 vendors at a midwestern food hub, an agent-based model (ABM) was created with distinct consumer personas characterizing the range of consumer priorities. A comparison study determined if the ABM behaved differently than a model based on traditional economic assumptions. Further simulation studies assessed the effect of changes in parameters, such as producer reliability and consumer profiles, on long-term food hub sustainability. The persona-based ABM model produced different and more resilient results than the more traditional way of modeling consumers. Reduced producer reliability significantly reduced trade; in some instances, a modest reduction in reliability threatened the sustainability of the system. Finally, a modest increase in price-driven consumers at the outset of the simulation quickly resulted in those consumers becoming a majority of the overall customer base. Results suggest that social factors, such as desire to support the community, can be more important than financial factors.
As demand for regionally produced food has increased, regional food hubs have helped to facilitate connections between consumers and small-scale food producers. However, food hubs often struggle to achieve the logistical and operational efficiencies that characterize conventional large-scale food distribution. In many cases, implementation of innovations adopted by conventional food distributors has proven to be challenging and even counterproductive for food hubs, due to their distinct business structure and mission. To address this problem, an empirical agent-based and discrete-event hybrid simulation model was developed to determine the effects of incorporating various efficiency-enhancing practices into food hub warehousing operations. The model was validated using data from a food hub in central Iowa. Experimental results demonstrate the potential usefulness of this model in supporting food hub managers’ operational planning decisions, as well as the effectiveness of incorporating agent-based and discrete-event simulation modeling paradigms to study warehousing operations.
Regional food hubs provide logistics services for small and mid-sized food producers, giving them the ability to reach larger markets and customers than they can reach on their own. However, once food hub managers have helped to establish connections between producers and new customers, they often find themselves cut out of the regional food supply chain when the farmers decide to sell their products directly to the customers, thereby avoiding the food hub’s service fees. Widespread disintermediation can eventually lead to food hub failure, which can disrupt the entire regional food system. This paper describes an agent-based model that incorporates reinforcement learning to study disintermediation behavior in a regional food supply network in Iowa. The model is designed to serve as a decision support tool for food hub managers, allowing them to simulate the effects of various supply chain management strategies on producer decision making and long-term system success.
Papers
- Krejci, C.C., Dorneich, M.C., & Stone, R.T. (2016), “Assessing Values-Based Sourcing Strategies in Regional Food Supply Networks: An Agent-Based Approach”, Journal on Policy & Complex Systems, Vol. 2, No. 2, pp. 21-48.
- Krejci, C.C., Stone, R.T., Dorneich, M.C., & Gilbert, S.B. (2015), “Analysis of Food Hub Commerce and Participation using Agent-Based Modeling: Integrating Financial and Social Drivers”, Human Factors (Special Issue: Human Factors Prize on Sustainability), Vol. 58, No. 1, pp. 58-79.
- Mittal, A. & Krejci, C.C. (2017), “A Hybrid Simulation Modeling Framework for Regional Food Hubs”, Journal of Simulation, Vol. 13, No. 1, pp. 28-43. doi:10.1057/s41273-017-0063-z
- Craven, T.J. & Krejci, C.C. (2016), “Assessing Management Strategies for Intermediated Regional Food Supply Networks”, Proceedings of the International Annual Conference of the American Society for Engineering Management, Charlotte, NC, October 26-29.
- Craven, T.J. & Krejci, C.C. (2016), “Effective Coordination in Regional Food Supply Chains”, Proceedings of the 2016 Industrial & Systems Engineering Research Conference, Anaheim, CA, May 21-24.
- Mittal, A., Zugg, M., & Krejci, C.C. (2016), “Improving Regional Food Hub Operational Efficiency with Lean Practices”, Proceedings of the 2016 Industrial & Systems Engineering Research Conference, Anaheim, CA, May 21-24.
- Mittal, A. & Krejci, C.C. (2015), “A Hybrid Simulation Model of Inbound Logistics Operations in Regional Food Supply Systems”, Proceedings of the 2015 Winter Simulation Conference, Huntington Beach, CA, December 6-9.
- Bora, H.D. & Krejci, C.C. (2015), “An Agent-Based Model of Supplier Management in Regional Food Systems (Work in Progress)”, Proceedings of the SCS Summer Simulation Multi-Conference, Chicago, IL, July 26-29.
- Bora, H.D. & Krejci, C.C. (2015), “Multi-Agent Simulation Modeling of Supplier Selection for Local Food Systems”, Proceedings of the 2015 Industrial & Systems Engineering Research Conference, Nashville, TN, May 30-June 2.