GOALI: Cooperation-based Optimization of the Industrial Gas Supply Chain

0931835 Maravelia为了在当今竞争激烈的环境中保持健康发展，化工企业必须通过同时优化多个层面的运营来有效运营其供应链（SC）。这是一项具有挑战性的任务，因为供应链是高度动态和相互关联的网络，通常由不同的决策者组成。因此，集中式办法无法在实践中实施，而现有的分散式办法只能产生次优的解决方案，不足以满足工业需要。因此，本项目的目标是为供应链（SC）运营规划开发一个基于合作的框架，该框架考虑本地决策，但同时考虑SC节点之间的相互作用。虽然最初的努力将集中在工业气体供应链上，但该框架应有效地解决广泛的制造业供应链中的运营规划问题。该项目的智力价值在于发现，开发和分析使用合作分布式框架优化大型，耦合，网络化供应链的方法。在制定这一框架时，方案执行机构将重点解决以下三个挑战：制定本地（节点）模型以及整个供应链的模型，准确地描述实际供应链节点之间的动态和互连.开发新的合作为基础的方法，以改善分布式动态供应链的决策。使用真实世界的数据评估这些方法，并制定成功实施这些方法的策略。在应对这些挑战时，PI将结合联合收割机现有的成果，并在优化，控制理论和博弈论领域开发新的成果。这些成果的整合将导致一个新的分布式决策框架，有可能改变未来的供应链。更广泛的影响：首先，拟议的研究将提高工业气体供应链的效率，以及其他制造业的供应链，从而提高美国公司的竞争力。其次，它有可能导致减少a）工业气体和钢铁制造等能源密集型部门的总体能源使用量，以及B）温室气体排放量。第三，基于合作的框架将整合优化，控制理论和博弈论的概念，从而推进分布式决策领域的最新技术。第四，这项研究的结果将用于开发教育材料，并将通过GNU Octave（一种由一个PI小组开发的免费传播语言）进行传播。最后，这项研究可以是变革性的，因为它将通过开发工具来量化优化整个供应链的影响，以促进这种分析，并开发方法来显示公司，各有各的财务目标，可以分享合作的利益。需要开展这类工作，以改变能源密集型工业的运作方式。

0931835MaraveliasTo remain healthy in today's competitive environment, chemical companies must operate their supply chain (SC) efficiently by simultaneously optimizing multiple levels of operation. This is a challenging task because supply chains are highly dynamic and interconnected networks, often comprised of different decision makers. Thus, centralized approaches cannot be implemented in practice, while existing decentralized methods yield suboptimal solutions and are insufficient to meet industrial needs. Accordingly, the goal of this project is to develop a cooperation-based framework for supply chain (SC) operation planning that considers local decision-making but at the same time accounts for the interactions between the nodes of the SC. While initial efforts will focus on the industrial gas supply chain, this framework should effectively address operational planning problems in a wide range of manufacturing supply chains.Intellectual merit: The intellectual merit of this project lies in the discovery, development, and analysis of methods for optimizing large, coupled, networked supply chains using a cooperative distributed framework. In developing this framework the PIs will focus on addressing the following three challenges:1. Formulate local (node) models as well as models for the entire supply chain that accurately describe the dynamics of and interconnections among nodes of practical supply chains.2. Develop novel cooperation-based methods for improved decision-making in distributed dynamic supply chains.3. Assess these methods using real-world data and develop strategies for successful implementation of the methods.In addressing these challenges, the PIs will combine existing as well as develop new results in the areas of optimization, control theory and game theory. The integration of these results will lead to a novel framework for distributed decision-making that has the potential to transform future supply chains.Broader Impact: First, the proposed research will improve the efficiency of the industrial gas supply chain, as well as supply chains in other manufacturing sectors, thus increasing the competitiveness of American companies. Second, it has the potential to lead to reductions in a) the overall energy usage in energy intensive sectors such as industrial gases and steel manufacturing, and b) in greenhouse gas emissions. Third, the cooperation-based framework will integrate concepts from optimization, control theory and game theory, thus advancing the state of the art in the area of distributed decision-making. Fourth, the results of this research will be used to develop educational material and will be disseminated through GNU Octave, a freely available dissemination language developed by the group of one of the PIs.Finally, the research can be transformative because it will quantify the impact of optimizing the overall supply chain by developing tools to facilitate such an analysis and developing methods to show how companies, each with their own financial objectives, can best share the benefit of such collaboration. Such work is needed to transform the operation of energy intensive industries.