Abstract :
We consider the simulation of constrained optimization problem, the (s, S) inventory system with stochastic lead-time and a service level constraint. We allow the orders to cross in time, which makes the problem more complicated. Bashyam and Fu (1998) first present this problem and obtained the answer by using perturbation analysis. Angun, Gurken, Hertog and Kleijnen (2006) studied the same question by using response surface method. The motivation for our work comes from the difference answers between them for the same model under the same situations. We establish the (s, S) inventory model by using Arean and find the estimators by OptQuest. In our conclusion, we give the true optimal estimator of (s*, S*) pairs estimated by Brute Force. Further, we prove that OptQuest can be used in solving the stochastic constrained optimization problem effectively. By testing estimatorspsila KKT conditions under large sample size procedure, we identify the best estimator.
Keywords :
inventory management; optimisation; stochastic processes; Arena; Brute Force; OptQuest; inventory system; service level constraint; stochastic constrained optimization; stochastic constrainted optimization problem; stochastic lead-time; Computational modeling; Computer science; Computer simulation; Constraint optimization; Response surface methodology; Statistical analysis; Stochastic processes; Stochastic systems; Technology management; Testing; arena; inventory system; optimization; simulation;
