CAREER: Distribution Resource Elasticity: A New Hierarchical Approach for On-Demand Distribution Platforms

这项学院早期职业发展(Career)补助金将支持通过创新和教育应对现代产品和服务分销挑战的研究，促进科学进步和促进国家繁荣。共享经济的出现使个人和小企业能够用按需供应补充传统的制造和服务市场。该项目的重点是通过同时向多个供应商提出定制建议，按需协调分散的分配资源的新方法。这些方法将通过利用原本未得到充分利用或闲置的供应能力来提高供应网络的效率。通过更灵活地使用供应商来提高能力，这种方法可以影响商业和非商业供应网络，提高电子商务的盈利能力，并建立一个新的按需志愿人员基础。与社区非营利组织和为行动受限客户提供的按需杂货递送系统的合作将提供测试案例，以验证开发的方法和机会产生积极的社会影响。经过有效沟通训练的工科本科生，将根据这项研究创建活动，以激励K-12学生攻读工程学。本科生和研究生将通过新的课程、课程、服务学习和研究经验与研究互动。该奖项支持在方法方面的基础研究，以实时协调按需分销平台的分散供应商，并量化供应商选择对平台效率、有效性和公平性的影响。新的双层优化方案将作为平台决策和供应商相互依赖的选择的函数来获取性能。新的优化模型和算法将指导平台的相互依赖的供应商建议，并对供应商选择所产生的结果进行分类。专门的精确方法将利用问题结构，而启发式方法将快速生成大规模解决方案。为了影响供应商的选择行为，薪酬决策将与推荐决策一起考虑。迭代技术将为被拒绝的请求设置补偿，确定供应商的表现应如何影响未来的平台决策和效用估计，何时部署平台资源，以及如何管理动态到达的请求和供应商。该奖项反映了NSF的法定使命，并已通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This Faculty Early Career Development (CAREER) grant will support research that addresses modern product and service distribution challenges through innovation and education, promoting both the progress of science and advancing national prosperity. The emergence of sharing economies has enabled individuals and small businesses to supplement traditional manufacturing and service markets with on-demand supply. This project focuses on novel methods to coordinate decentralized distribution resources on-demand through customized recommendations made to multiple suppliers simultaneously. Such methods will improve the efficiency of the supply network by tapping into otherwise underutilized or idling supply capacity. By increasing capacity through more flexible use of suppliers, this approach can impact both commercial and non-commercial supply networks, improving e-commerce profitability and enabling a new on-demand volunteer base. Collaborations with community nonprofits and on-demand grocery delivery systems for mobility-restricted clients will provide test cases to validate the developed methods and opportunities for positive societal impact. Undergraduate engineering students, trained in effective communication, will create activities informed by this research to inspire K-12 students to pursue engineering. Undergraduate and graduate students will interact with the research via new curriculum, classes, service learning, and research experiences. This award supports fundamental research in methods to coordinate decentralized suppliers in real-time for on-demand distribution platforms and to quantify the impact of supplier choice on platform efficiency, effectiveness, and equity. New bi-level optimization formulations will capture performance as a function of both the platform's decisions and suppliers' interdependent choices. New optimization models and algorithms will guide platform's interdependent supplier recommendations and categorize responses to outcomes created by supplier choice. Specialized exact approaches will exploit problem structure, while heuristic approaches will generate large-scale solutions quickly. To affect suppliers' selection behaviors, compensation decisions will be considered jointly with recommendation decisions. Iterative techniques will set compensation for rejected requests, determine how supplier performance should influence future platform decisions and utility estimates, when to deploy platform resources, and how to manage dynamically arriving requests and suppliers.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.