ADAM: A web platform for graph-based modeling and optimization of supply chains.
Yicheng Hu, Weiqi Zhang, Philip Tominac, Margaret Shen, Dilara Gorëke, Edgar Martín-Hernández, Mariano Martín, Gerardo J Ruiz-Mercado, Victor M Zavala
Author Information
Yicheng Hu: Department of Chemical and Biological Engineering, University of Wisconsin-Madison, 1415 Engineering Dr, Madison, WI 53706, USA.
Weiqi Zhang: Department of Chemical and Biological Engineering, University of Wisconsin-Madison, 1415 Engineering Dr, Madison, WI 53706, USA.
Philip Tominac: Department of Chemical and Biological Engineering, University of Wisconsin-Madison, 1415 Engineering Dr, Madison, WI 53706, USA.
Margaret Shen: Department of Chemical and Biological Engineering, University of Wisconsin-Madison, 1415 Engineering Dr, Madison, WI 53706, USA.
Dilara Gorëke: Department of Chemical and Biological Engineering, University of Wisconsin-Madison, 1415 Engineering Dr, Madison, WI 53706, USA.
Edgar Martín-Hernández: Department of Chemical Engineering, University of Salamanca, Plza. Caídos 1-5, Salamanca 37008, Spain.
Mariano Martín: Department of Chemical Engineering, University of Salamanca, Plza. Caídos 1-5, Salamanca 37008, Spain.
Gerardo J Ruiz-Mercado: Center for Environmental Solutions and Emergency Response, U.S. Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, USA.
Victor M Zavala: Department of Chemical and Biological Engineering, University of Wisconsin-Madison, 1415 Engineering Dr, Madison, WI 53706, USA.
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.
