An evaluation of heuristics for allocating components to kits in small-lot, multi-echelon assembly systems

The kitting problem in multi-echelon assembly systems is to allocate on-hand stock and anticipated future deliveries to kits to minimize total cost, consisting of job earliness, job tardiness, and in-process holding costs. This paper describes the kitting problem and compares the performance of three heuristics, two that are commonly used in industry and a new one, to resolve it. Computational experience demonstrates that the new heuristic outperforms the others, finding the optimal solution in 16 of 24 test problems and averaging just 0.6% above the optimum for the 24 problems. It is expected that the new heuristic will find application in large-scale problems encountered in industry. Solutions will facilitate time-managed flow control, prescribing kitting decisions that promote cost-effective performance to schedule.