Probabilistic cost estimation in advance of production in a computerized manufacturing system through stochastic geometric programming

A mathematical model for stochastic cost optimization has been developed. The model contains cost terms such as inventory cost, penalty cost for due date violation, and the machining cost. The probable range of cost has been estimated by a stochastic geometric program. If an exact solution is desired, a two stage stochastic geometric program has to be solved. This is mathematically tedious and requires great computational effort. However, managers are often concerned with a policy decision which can be based on the probable lower and upper bounds on the cost function. The probability level on the lower bound of cost has been calculated through the theory of error propagation. This approach is explained through an example.