Discrete-event simulation optimization: a review of past approaches and propositions for future direction

Over the past twenty years, a significant body of work has been undertaken on the topic of methods and approaches to optimizing discrete-event simulation models. Then, as is now, one of the greatest challenges in optimizing discrete-event simulations is the inability to precisely identify "the" optimal solution to a given system model. This is especially the case as the feasible solution space expands. Also over the past twenty years, computational speed has increased, computing and modeling costs have decreased and theoretical developments in the field of simulation optimization have emerged. Yet a divide appears to be widening. Recent literature indicates a lack of new, innovative approaches to optimizing large scale discrete-event simulation models as well as an absence in addressing the growing chasm between the simulation modeling, optimization and outcome improvement processes. Many of the studies and advances undertaken in the early to mid-90's are those still cited today when discussing simulation optimization. This paper discusses and provides an overview of theoretical and methodological directions in discrete-event simulation optimization. In addition, it suggests areas of study for advancing the field. It is proposed that advances should move the field of study and application in the direction of blurring the boundaries between simulation modeling, optimization and change implementation communities instead of widening the gaps.