This paper develops an efficient method to solve a typical combinatorial optimization problem that is frequently encountered when designing high levels of productivity and quality with a reasonable cost. Recent industrial applications have critical quality requirements that are not taken into account by the majority of methods proposed in the literature. In this paper, we explore the impact of adding these quality constraints on the system performance. We use a fast cost calculation model to solve the optimal buffer sizing problem in unreliable production lines simultaneously with the quality control problem constraints. The system studied in this contribution consists of n machines, n fixed-size buffers and m inspection stations in series. The objective is to minimize combined storage and shortage costs, and also to specify the optimal number and location of those inspection stations in the system. We combine a multilevel hybrid search method to identify search regions with promising locations of inspection stations and an exact method to optimize the assignment of buffer sizes for each location. Numerical results on test problems from previous research are reported. This approach reduces the solution time by more than 97% in some cases and allows a huge test problem with 30 machines to be solved.
Published September 2015 , 20 pages