Print Email Facebook Twitter Applying Constraint Programming To Enterprise Modelling Title Applying Constraint Programming To Enterprise Modelling Author Andringa, Sytze (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Yorke-Smith, N. (mentor) van Essen, J.T. (graduation committee) van der Wal, C.N. (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science Date 2021-07-02 Abstract Enterprise Modelling (EM) is the process of producing models, which in turn can be used to support understanding, analysis, (re)design, reasoning, control and learning about various aspects of an enterprise. Various EM techniques and languages exist, and are often supported by computational tools, in particular simulation. The goal of this thesis is to study the effects and advantages of applying constraint programming (CP) to EM. To the best of my knowledge, no previous study has explicitly combined EM and CP. On the topic of applying CP to EM, this thesis explains where it can be applied, as well as its requirements and advantages. Furthermore, it explains a possible approach where a neural network, trained on a simulation model that represents an enterprise model, is embedded into a constraint program. This approach is supported with experiments, that show typical business objectives can be embedded in a constraint program and find solutions to it in a multi-objective context. The main conclusion is that due to CP being a declarative programming technique, business constraints and goals can be effectively modelled into a constraint program, making the approach understandable and intuitive for business analysts to use. This thesis argues alternative approaches to apply CP to EM can also be realised. Some of these, as well as improvements over the proposed method, are also discussed. Subject Enterprise ModellingConstraint Programming (CP)machine learningsimulationOptimisationsocio-technical systems To reference this document use: http://resolver.tudelft.nl/uuid:7d67baa1-6e28-407a-9cab-9cd67e592d8e Bibliographical note https://github.com/SytzeAndr/EM_to_CP Repository link GitHub repository with supplementary code Part of collection Student theses Document type master thesis Rights © 2021 Sytze Andringa Files PDF MscThesis_Andringa_EM_CP_final.pdf 3.11 MB Close viewer /islandora/object/uuid:7d67baa1-6e28-407a-9cab-9cd67e592d8e/datastream/OBJ/view