Design of Multi-stage Adaptive Kanban System using Simulated Annealing algorithm

The Traditional Kanban System (TKS) with a fixed number of cards does not work satisfactorily in an unstable environment. In the adaptive kanban type pull control mechanism, the number of kanban is allowed to change with respect to the inventory and backorder level. It is required to set the threshold values at which cards are added or deleted, which is a part of the design. Previous studies used the local search and meta-heuristic methods to design the Adaptive Kanban System (AKS) for a single stage. In the multi-stage system the cards are circulated within the stage and their presence at designated positions signal to the neighbouring stages about the inventory. In this work, an improved model of the multi-stage system as compared to the traditional and AKS is developed. A Simulated Annealing (SA) algorithm based search is employed to set the parameters of the system. The results are compared with the TKS and signs of improvement were found.

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