ABSTRACT
In this chapter, the authors give a detailed discussion of a simulation solution for a realistic optimization problem. They focus on the simulation’s design, analysis, and programming and simplify the real-world problem. The authors cover the details of the data analysis in the efficient statistical design method, and give final recommendations on choice. Methods for optimizing systems using simulation are not static, but are constantly developing. For example, an exciting new method called “simulated annealing” burst upon the scene in the 1980s. However, the simulated annealing method seems very adept at avoiding a common flaw of optimization methods, namely the tendency to become trapped in local optima (versus a global optimum). Edissonov presented a new optimization method, which seeks optima of a multi-parameter objective function, has been compared with many other random search methods on established test functions and has been found to be best for 3 or more parameters.
