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This work focuses on the supply chain tactical planning problem in an uncertain and turbulent environment. In order to minimize the effect of disturbances due to these uncertainties, we propose an approach based on dynamic constraint satisfaction problems. This is to plan production by searching the best compromise between available decision- making levers for capacity and production costs by adopting a dynamic process, which enables data update at each planning step. Our approach is evaluated by simulation under uncertain data. For this, we have developed various experiments related to the variation of customer demand and resource capacity. All the experiments are carried out by two different methods: a method based on a static CSP and a method based on a dynamic CSP. The performance of a planning solution is reported through stability measurement. Results of experiments confirm the performance of the method based on a dynamic CSP.
supply chain, planning, dynamic constraint satisfaction, stability.
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