Optimization of Operations Resources via Discrete Event Simulation Modeling

The resource levels required for operation and support of reusable launch vehicles are typically defined through discrete event simulation modeling. Minimizing these resources constitutes an optimization problem involving discrete variables and simulation. Conventional approaches to solve such optimization problems involving integer valued decision variables are the pattern search and statistical methods. However, in a simulation environment that is characterized by search spaces of unknown topology and stochastic measures, these optimization approaches often prove inadequate. In this paper, we have explored the applicability of genetic algorithms to the simulation domain. Genetic algorithms provide a robust search strategy that does not require continuity and differentiability of the problem domain. The genetic algorithm successfully minimized the operation and support activities for a space vehicle, through a discrete event simulation model. The practical issues associated with simulation optimization, such as stochastic variables and constraints, were also taken into consideration. Introduction The design of complex space systems, such as a launch vehicle, has historically emphasized the performance requirements aspect. However, declining budgets and global competition of recent years has prompted the need for economically competitive systems, designed for operability and supportability as well. It has been shown that Operations and Support (O&S) activities account for 60% to 80% of life cycle costs of reusable space systems. Therefore, in order to minimize life cycle costs, it is essential to study and optimize O&S resources in the early design phase. The complex interaction between various O&S resources can be studied through a stochastic discrete event simulation model. For a particular vehicle and space program, the model can be used to predict the number of missions flown and the mean vehicle turntime, for user-specified resources. However, the simulation model cannot directly be used to minimize the O&S resources. Currently, this problem is addressed by manually varying the input variables of the simulation, one at a time, until the resource allocation seems to be at a minimum level. Minimizing the resources for a launch vehicle constitutes an optimization problem involving integer variables, which is a https://ntrs.nasa.gov/search.jsp?R=20040110937 2017-09-13T22:29:56+00:00Z