This is a proceedings volume of a workshop on "Computationally intensive methods in Simulation and Optimization". The purpose of the meeting was to review and evaluate newly developed methods for combining simulation and optimization. These methods are used for decision problems about stochastic systems like production systems or communication networks, which are too complex for being modeled in an analytic way. A simulation model for such a system is the basis for an efficient use of recursive stochastic optimization techniques. The volume contains selected papers from three areas: 1. Gradient techniques for discrete event simulation models 2. Stochastic optimization methods 3. Efficient random generation methods The book contains articles dealing with competing methods like the score method, perturbation analysis and experimental design techniques. For the first time, a comparision between these techniques is made.
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