Collaborative Research: Mitigating the Cost of Anarchy in Complex Supply Chain Systems

该项目支持一项合作研究计划，该计划将提高对实践中复杂分散供应链运作的有效协调的理解。虽然分散的供应链允许公司在执行特定功能方面变得熟练和高效，但单个供应链功能的有效执行并不能确保整个系统尽可能高效地运行。特别是对于分散的系统，不同供应链阶段的激励往往是不一致的。尽管每个阶段都有很高的效率，但这种激励失调可能而且经常导致系统中本可避免的损失。各阶段之间的协调成为减轻这些损失的关键因素。这个项目的主要目标是开发有效的、直观的和高效的可实现的协调机制，以提高复杂操作系统的性能和效率。该项目将强调可以广泛有效地应用于涉及活动成本规模经济的工业系统的解决方案。通过评估一系列直观且易于实施的方案，这项工作将有助于提高对实际和复杂供应链运营环境中有效协调机制结构的理解。通过开发具有非线性收入和成本函数的复杂系统中协调操作的新决策模型，该项目将有助于了解组织如何能够(i)在具有现实成本和需求特征的分散系统中实现协调操作，以及（ii）从系统角度理解操作决策的含义。由此产生的建模、分析和算法开发也将有助于应用参数优化理论和大规模问题解决的进步。除了在复杂系统中实现简化操作的经济影响之外，这可以为公司创造巨大的经济价值，这项工作将有助于加深我们对以分散方式运行的复杂系统的理解。

This project supports a collaborative research program that will lead to an improved understanding of effective coordination of complex decentralized supply chain operations in practice. While decentralized supply chains permit firms to become adept and efficient at performing specific functions, efficient performance of individual supply chain functions does not ensure that the entire system operates as efficiently as possible. For decentralized systems in particular, incentives at different supply chain stages are often misaligned. Despite a high degree of efficiency within each stage, this incentive misalignment can and often does lead to avoidable losses in the system. Coordination among stages becomes a critical factor in mitigating these losses. The main goal of this project is to develop effective, intuitive, and efficiently implementable coordination mechanisms for improving performance and efficiency in complex operations systems. The project will emphasize solutions that can be applied broadly and effectively in industry to systems involving economies-of-scale in activity costs. By evaluating an array of intuitive and easily implemented schemes, this work will lead to an improved understanding of the structure of effective coordination mechanisms in practical and complex supply chain operations environments. By developing new decision models for coordinating operations in complex systems with nonlinear revenue and cost functions, this project will contribute to the state of knowledge on how organizations can (i) achieve coordinated operations in decentralized systems with realistic cost and demand characteristics, and (ii) understand the implications of operations decisions from a systems view. The resulting modeling, analysis, and algorithmic development will also contribute advances in applied parametric optimization theory and large-scale problem solving. Beyond the economic impact of enabling streamlined operations in complex systems, which can create substantial economic value for firms, this work will serve to deepen our understanding of complex systems that operate in a decentralized manner.