Thesis

Exploring frameworks for mixing Discrete Event Simulation and System Dynamics methods in theory and in practice

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Awarding institution
  • University of Strathclyde
Date of award
  • 2013
Thesis identifier
  • T13553
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Abstract
  • Discrete Event Simulation (DES) and System Dynamics (SD) are popular modelling methods that have a broad range of applications. Both have been successfully applied to similar situations and are mixed with other Operational Research methods to provide insight into the behaviour of systems for organisations. Motivated by support from within the research communities, questions have been raised as to whether the two methods could or should be combined, and if so when and how they could be mixed. Comparing the methods reveals points of dissimilarity but also of commonality. Consequently, this research considers how mixing these methods may contribute insights into real life problem systems. The multimethodology and simulation literatures clarify how methods could be theoretically mixed and what modellers are doing in practice. Mixed method designs developed from this literature are proposed. Their applicability to the real world was explored through mixed DES and SD example projects, leading to a proposed toolbox of guidelines to reflect upon when considering mixing methods. Inspired by similarities and differences in the DES and SD model development processes, a model development framework was proposed. The toolbox of designs was placed at its heart to encourage reflection on mixing methods from project exploration and design to analysis and reporting. These frameworks were developed during an action research project within the Beatson Oncology Centre. This enabled their applicability throughout the cycles of model development to be explored in the context of a real, complex system. The final outcome of this research is a framework to assist mixing methods, through a model development process and mixed method designs. This encourages reflection on how methods are used in a project and enables clear representation of work conducted to facilitate knowledge transfer. Lessons from the project and wider contributions of mixed DES and SD modelling are proposed.
Resource Type
DOI
Date Created
  • 2013
Former identifier
  • 1001094

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