Simulation Optimization Using Simulated Annealing: A Network-based Implementation and Study of CoolingSchedules

Simulation optimization of complex systems with noisyparameter spaces can become computationally expensiveon a single processor system. This book discussesconstruction of software for solving optimizationproblems by distributing the work load among severalprocessors residing on a network. Open sourcerepositories are used for the development of thissoftware. The Simulated Annealing algorithm is usedto search the parameter space for optimization.Application of the software to stochastic anddeterministic problem scenarios is closely examined.Since the convergence of the simulated annealingalgorithm depends on the choice of annealingparameters, different types of simple and elaboratecooling schedules are applied to problem instancesand their impact on the quality of convergence isassessed.

MSE in Industrial Engineering from the University of Alabama inHuntsville (UAHuntsville). PhD candidate at UAHuntsville withresearch interests in simulation optimization, experimentaldesign and multivariate statistical analysis.