A genetic approach to Kanban assignment problems

In this paper, an effective genetic Kanban assignment algorithm is developed to determine the number of Kanbans that should be assigned to each of the production stages in a deterministic capacitated serial just-in-time production system. The objective is to minimize the cost of inventory of the system. An integer programming model is used to describe the production operation of the system. The algorithm is described in detail and its effectiveness is illustrated by solving a typical Kanban assignment problem. The performance of the algorithm is further illustrated by using a set of randomly generated test problems.