A Robust Multi-Objective Lead Time Control Problem in Complex Assembly Systems

In this paper, a robust multi-objective model to optimally control the lead time of a complex assembly system is introduced. The system is modeled as an open queue network, whose service stations represent manufacturing or assembly operations. It is assumed that the products arrive independently according to a Poisson process. In each service station, there is either one or infinite number of servers with exponentially distributed processing time. Each service station produces uncertain but limited number of scraps which are independent from the other service stations. The transport times between the service stations are independent random variables with generalized Erlang distribution. Addressing the data uncertainty, the problem is formulated as a robust multi-objective optimal control problem that involves three types of conflicting objective functions. The types of objective functions are the total operating costs of the system per period, the average lead time and the variance of the lead time. Finally, we use the goal attainment method to solve a discretetime approximation of the original problem to obtain the optimal service rates of the problem.