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ADAM: A web platform for graph-based modeling and optimization of supply chains
Citation:
Hu, Y., W. Zhang, P. Tominac, M. Shen, D. Göreke, E. Martín-Hernández, M. Martín, Gerardo J. Ruiz-Mercado, AND V. Zavala. ADAM: A web platform for graph-based modeling and optimization of supply chains. COMPUTERS AND CHEMICAL ENGINEERING. Elsevier Science Ltd, New York, NY, 165:107911, (2022). https://doi.org/10.1016/j.compchemeng.2022.107911
Impact/Purpose:
Many communities are looking for feasible solutions to address quality of life challenges, ecological impairments, and economic impacts caused by the inefficient management of organic waste. Organic waste is a source of nutrient releases in soil and receiving waters. Nutrient releases contribute to the eutrophication of fresh and marine waters, harmful algal blooms (HABs), toxins release, and hypoxia due to algae biomass decomposition. This peer-reviewed manuscript describes a web-based platform for the design, modeling, and optimization of supply chains and their application for the sustainable materials management of livestock waste. This web platform, called ADAM (Advanced Decision-making and Management Tool), provides stakeholders the capabilities to simultaneously maximize economic benefits and minimize environmental impacts. ADAM combines techno-economic processing data, nutrient sources, geospatial information, and potential products. A platform’s solution provides community-relevant decision-makers an optimal supply chain for materials management by giving the best locations and selection of technology valorization placement, value-added products, and material transportation routes while minimizing unintended consequences across a geographical area. Also, this web platform enables stakeholders to perform an economic feasibility evaluation of diverse types of material management incentives obtained at the federal and state levels. For nutrient pollution problems, this platform offers the capability of determining profitable prices of recovered products, regional nutrient balances, and examining spatiotemporal environmental impacts.
Description:
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.
URLs/Downloads:
DOI: ADAM: A web platform for graph-based modeling and optimization of supply chains
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