SIMULA tool for simulation-based optimization

The paper demonstrates the use of the SIMULA package OPTSIM that has been designed for teaching simulation-based optimization of discrete systems. Two optimization algorithms are implemented in several versions. For continuous optimization a modified Nelder-Mead moving simplex algorithm has been implemented. Local search algorithm is used for integer and mixed integer optimization. As OPTSIM is a subclass of another SIMULA class QUESIM for Simulation of queuing systems, simulation based evaluation of objective and constraint functions is relatively easy. Two optimization examples are used to demonstrate the basic ideas.