Optimisation in Discrete-event simulation models

Abstract

Discrete-event simulation is a tool used to simulate and analyse complex real-world systems. As a system gets more complex the number of parameter variations can increase, making it difficult for the user to accurately predict an optimal solution. Optimisation methods are mathematical algorithms that are specialised in finding optimal solutions for a given problem. A combination of discrete-event simulation and optimisation methods could result in a more efficient problem-solving process which has the possibility of providing more optimal solutions. This thesis uses a case study methodology that includes a literature study and a qualitative study to assess the possibilities of using optimisation tools in a simulation setting in an organisation. Optimisation tools in discrete-event simulation software exists in several available software and all of the ones studied in this thesis utilise evolutionary algorithms for optimisation calculations. This thesis handles the importance of finding the right use-case for the implementation of simulation optimisation in a project. A decision tree was created to help users navigate questions one could ask themselves when deciding whether optimisation is suitable in their projects or not.