With the advance of computing power, heuristic algorithms are gaining popularity since they mainly increase the efficiency in finding better solutions for hard problems, mostly combinatorial optimization one. However, heuristic algorithms often need setting parameter values in many situations, and the choices of parameter value set may affect solution quality and calculation time, as indicated in much literature. Naïve user of those heuristics sees parameter setting as a daunting task. Without sacrificing the value of heuristics, the parameter setting can be thought of as finding a best design; and the best design is the one that assist the heuristic in finding the best solution. In the study, Simulated Annealing (SA) heuristic algorithm with Optimal Computing Budgeting Allocation (OCBA) is suggested to determine better SA parameters and optimal solution. Standard testing examples were tested to compare the solution quality of OCBA-SA and SA only. OCBA-SA was also applied to a material inventory problem to find optimal inventory level under uncertain demands.