Modeling and optimization are essential tasks that arise in the analysis and design of supply chains (SCs). SC models are essential for understanding emergent behavior such as transactions between participants, inherent value of products exchanged, as well as impact of externalities (e.g., policy and climate) and of constraints. Unfortunately, most users of SC models have limited expertise in mathematical optimization, and this hinders the adoption of advanced decision-making tools. In this work, we present ADAM, a web platform that enables the modeling and optimization of SCs. ADAM facilitates modeling by leveraging intuitive and compact graph-based abstractions that allow the user to express dependencies between locations, products, and participants. ADAM model objects serve as repositories of experimental, technology, and socio-economic data; moreover, the graph abstractions facilitate the organization and exchange of models and provides a natural framework for education and outreach. Here, we discuss the graph abstractions and software design principles behind ADAM, its key functional features and workflows, and application examples.

建模和优化是供应链 (SC) 分析和设计中必不可少的任务。SC 模型对于理解诸如参与者之间的交易、所交换产品的内在价值以及外部性（例如政策和气候）和约束的影响等紧急行为至关重要。不幸的是，大多数 SC 模型的用户在数学优化方面的专业知识有限，这阻碍了高级决策工具的采用。在这项工作中，我们介绍了ADAM，这是一个能够对 SC 进行建模和优化的网络平台。ADAM通过利用直观且紧凑的基于图形的抽象来促进建模，这些抽象允许用户表达位置、产品和参与者之间的依赖关系。亚当模型对象充当实验、技术和社会经济数据的存储库；此外，图形抽象有助于模型的组织和交换，并为教育和外展提供自然框架。在这里，我们讨论了ADAM背后的图形抽象和软件设计原则、它的关键功能特性和工作流程，以及应用示例。