Abstract
The main element of just-in-time production system is kanban and the number of kanban influences the product inventory level. This research studies the cellular manufacturing system controlled by kanban mechanism which defective items are produced in any production run of each product and rework is carried out to transform them into serviceable items. In each cycle after the normal production of each product, the machine is setup for the rework process. In this paper, a mixed-integer nonlinear programming (MINLP) model in order to minimize total cost was developed to determine number of kanban, batch size, and number of batches. To avoid the large computational time in optimal solution, a particle swarm optimization (PSO) and simulated annealing (SA) algorithms as metaheuristic methods are used for solving a large MINLP. Some problems are solved by PSO and SA and performance of the PSO and the SA is evaluated by comparing their results with the optimal solution. It is shown that both PSO and SA result in a near-optimal solution but the PSO algorithm gives a better performance than the SA method.
Published Version
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