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Simulation Optimization via Metamodeling Approach

Simulation optimization (SO) is the process of finding the best set of input variable values without explicitly evaluating each feasible set of these input variable values given an output criterion (Law, 2007; Fu, 1994). Input variables are called (controllable) inputs, parameter settings, values, variables, (proposed) solutions, designs, configurations, or factors (in design of experiments terminology). Outputs are called performance measures, criteria, or responses (in design of experiments terminology). Some of the outputs are used to form an objective function, and there is a constraint set on the inputs. Our aim is to optimize the objective function given below: