Simulation modelling is a prevailing technique to analyse complex systems when closed-form analytical models provide poor estimations or do not exist at all because of the modelling assumptions and system complexities. Simulation models enable decision-makers to set-up "what-If" questions about the effects of alternative pre-specified decisions on the system performance, but they are not equipped with search techniques to find and suggest optimal decision(s). Thus, simulation models are combined with optimisation algorithms (e.g., metaheuristics and/or exact methods) to find optimal or near optimal decisions for complex problems. Such a coupling is known as 'simulation-based optimisation' in decision-making framework. Recent advances have incorporated simulation-based optimisation with 'exploratory modelling' (e.g., multi-objective robust optimisation) to identify 'robust' decisions under uncertainty; decisions which can remain effective even if the future does not unfold as estimated in the initial assumptions.
With recent increases in the computational power of computers, there have been growing usage and applications of simulation, optimisation, and exploratory modelling across a variety of domains including defense applications, environmental systems, communication networks, supply chains, and healthcare systems. The goal of this special session is to provide recent developments in these areas and their intersection, theoretically as well as in real-world applications. Papers are invited in, but are not limited to, the following areas:
Key topics: Decision making, Extended simulation framework, Simulation-based optimisation, Exploratory modelling