Simulation and Optimization

<p style="margin-top:0.5em;margin-bottom:0.5em;line-height:inherit;white-space:normal;"> Simulation-based optimization&nbsp;integrates optimization techniques into simulation analysis. Because of the complexity of the simulation, the objective function may become difficult and expensive to evaluate. Once a system is mathematically modeled, computer-based simulations provide information about its behavior. Parametric simulation methods can be used to improve the performance of a system. In this method, the input of each variable is varied with other parameters remaining constant and the effect on the design objective is observed. This is a time-consuming method and improves the performance partially. To obtain the optimal solution with minimum computation and time, the problem is solved iteratively where in each iteration the solution moves closer to the optimum solution. Such methods are known as ‘numerical optimization’ or ‘simulation-based optimization’. </p> <p style="margin-top:0.5em;margin-bottom:0.5em;line-height:inherit;white-space:normal;"> <br /> </p> <p style="margin-top:0.5em;margin-bottom:0.5em;line-height:inherit;white-space:normal;"> In the present book, fifteen typical literatures about simulation and optimization published on international authoritative journals were selected to introduce the worldwide newest progress, which contains reviews or original researches on Computational Fluid Simulation, Flow Optimization, Derivative-free optimization methods, Dynamic programming, Streamline Simulation, Simulation-Driven Optimization,&nbsp;etc. We hope this book can demonstrate advances in simulation and optimization as well as give references to the researchers, students and other related people. </p>