Order-To-Cash (OTC)is an interface where propose a mathematical programming approach to optimize the business process transactions in digital supply chains. Five scheduling models from the Process Systems Engineering (PSE) area are applied to schedule the processing of orders in a simplified Order-To-Cash (OTC) business process, which is modeled as a multistage network with parallel units (agents).
The models are compared and scaled to select those that are more suitable to this application.
The continuous-time general precedence model provides an accurate representation of the real system
and performs well for small instances. The discrete-time State-Task Network (STN), however, proves most
efficient in terms of tractability, despite the well-known limitations resulting from discretizing time. The
tightness of the linear programming (LP) relaxations in the discrete-time STN framework, as well as the
ability of commercial solvers to perform preprocessing and apply heuristics to the STN formulation, enables finding near optimal solutions quickly even for larger instances.
OTC is based on the model developed by Hector D. Perez, Satyajith Amaran, Esra Erisen, John M. Wassick, Ignacio E. Grossmann, "Optimization of extended business processes in digital supply chains using mathematical programming", Computers & Chemical Engineering
Volume 152, September 2021, 107323; and has been developed by Rosanna Franco under the supervision of Ignacio E.Grossmann.
Overview of OTC process
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