TY - DATA
T1 - Supplementary code to the paper: Flexible Enterprise Optimization With Constraint Programming
PY - 2021/12/15
AU - Sytze Andringa
AU - Neil Yorke-Smith
UR - https://data.4tu.nl/articles/software/Supplementary_code_to_the_paper_Flexible_Enterprise_Optimization_With_Constraint_Programming/17060642/1
DO - 10.4121/17060642.v1
KW - Constraint programming (Computer science)
KW - deep learning
KW - Enterprise engineering
KW - simulation
KW - optimization
N2 - This repository contains experimental data for the experiments performed in "Flexible Enterprise Optimization With Constraint Programming". The experiments are based on how enterprise models can be "solved" through CP. Due to page limit reasons, not all experiments were discussed in the paper.<br>The experiments in this repository can be divided into three categories.<br>1. Petri-nets. Here, petri net models based on enterprise models are solved through MiniZinc.2. Netlogo simulation + Neural network. Here, neural networks are trained on NetLogo simulation models. Then, these neural networks are embedded into MiniZinc, and used to find solutions to it in a multi objective sense.3. Other experiments. Here, a simple supply chain of a pizza restaurant, as well as a hospital case (FHCC) that was based on a DEMO model, are formulated as a CP model. These experiments are not dicussed in the thesis.
ER -