Optimizing Operations and Logistics Support Using Opus Evo

Understanding the interplay between the reliability and maintainability of a fleet of complex systems, the logistics support organization, and the operational scenario, is vital from a short-term tactical perspective, as well as a strategic long-term Life Cycle Cost (LCC) perspective, as each of these areas has a direct impact on one another. A common method to analyze and evaluate the performance of the overall scenario, as well as getting insights into problem areas, bottlenecks and to perform analysis-of-alternatives is to use discrete event simulation.In this paper we present a methodology to extend a discrete event simulation tool with inherent optimization capabilities. Using established heuristic optimization techniques, we perform simulation driven optimization that optimizes parameters in the modeled scenario. Optimized parameters typically include:• sparing strategies such as inventory levels and locations • resource quantities and location • deployed system quantities to fulfill mission requirements • scheduled maintenance times. • transportation and resource schedules.A case study is presented that utilizes Opus Evo, an application that extends the commercial off the shelf Opus Suite with capability to perform heuristic optimization using simulation.