Collaborative Research: Designing Responsive Product and Service Fulfillment Networks using Dynamic Adaptive Modeling

这个合作研究项目解决了一个新的大规模优化模型，称为网络设计与服务保证（NDSG），同时结合收入，成本和服务（端到端延迟）的考虑。 NDSG模型虽然具有重要的实际意义，但无论从理论上还是计算上都很难求解。 我们的目标是开发和测试有效的解决方案的程序，使用国家的最先进的优化技术，可以利用NDSG问题的特殊数学结构。 因此，该项目需要进行理论和实证研究，包括开发和表征替代问题公式，分析其结构特性，设计专门的解决方案算法，并使用实际数据测试这些方法。 为了解决这个问题，一个新的家庭的优化算法，动态地重新制定的问题，并相应地适应的解决方案相结合的分解和模型增强技术将被调查。 预计核心研究的贡献-一个新的建模范式，一个新的解决方案的方法，和算法的实现-也将扩展到其他大规模的优化模型。 在新的网络经济中，通信和实物分配能力已变得至关重要。 组织已经开始依赖这些能力来建立紧密集成的合作伙伴关系，从而有效地满足产品和服务的不同市场需求。 信息或货物流动的延误或故障不仅会对供应链造成破坏性后果，还会对紧急行动、空中交通管制和金融系统等服务造成破坏性后果。 关于支持协调和合作所需的通信和分配网络的配置的决策具有战略重要性，因为它们需要数十亿美元的巨额投资，并且因为网络的拓扑设计在很大程度上决定了它可以提供的服务水平。 因此，优化工具在实践中被广泛用于设计产品和服务履行网络，网络设计仍然是一个非常活跃的研究领域。 设计最优的网络配置需要在相互冲突的目标之间进行复杂的权衡，如最大化利润率，确保足够的资源利用率，提高服务水平，等等。经典的优化模型，主要集中在成本最小化，往往设计稀疏网络，利用规模经济，但在服务和可靠性方面并不稳健。该项目将为研究生提供进行论文研究的机会，并丰富研究生课程的优化和操作建模。

This collaborative research project addresses a new large-scale optimization model, called Network Design with Service Guarantees (NDSG), that simultaneously incorporates revenue, cost, and service (end-to-end delay) considerations. Though of immense practical significance, the NDSG model is very difficult to solve both from theoretical and computational perspectives. The goal is to develop and test effective solution procedures using state-of-the-art optimization techniques that can exploit the NDSG problem's special mathematical structure. Accordingly, the project entails both theoretical and empirical investigations, including developing and characterizing alternative problem formulations, analyzing their structural properties, designing specialized solution algorithms, and testing these methods using realistic data. To solve the problem, a new family of optimization algorithms that dynamically reformulates the problem, and correspondingly adapts the solution approach by combining decomposition and model strengthening techniques will be investigated. It is expected that the core research contributions-a new modeling paradigm, a novel solution approach, and algorithmic implementation-will also extend to other large-scale optimization models. Communication and physical distribution capabilities have become critical in the new networked economy. Organizations have come to rely on these capabilities to establish tightly integrated partnerships that can effectively serve diverse market needs for products and services. Delays or failures in the movement of information or goods can have debilitating consequences not only for supply chains but also for services such as emergency operations, air traffic control, and financial systems. Decisions regarding the configuration of communication and distribution networks needed to support coordination and collaboration have strategic importance both because they entail massive investments of billions of dollars and because a network's topological design largely determines the level of service it can provide. Consequently, optimization tools are widely used in practice to design product and service fulfillment networks, and network design continues to be a very active research area. Designing optimal network configurations entails complex tradeoffs between conflicting objectives such as maximizing profitability, ensuring adequate resource utilization, improving service levels, and so on. Classical optimization models, which focus primarily on cost minimization, tend to design sparse networks that exploit economies of scale but are not robust in terms of service and reliability. The project will provide opportunities for graduate students to conduct thesis research, and enrich graduate courses in optimization and operations modeling.