A DSS for production planning

This paper presents a decision support system designed to aid the production planner in choosing the values of the principal parameters governing just-in-time manufacturing. The DSS uses a knowledge base composed of data from simulations of the production of the entire product line under systematically varied conditions. The planners may add data from actual production experience as it is obtained. The stochastic dominance outranking method of Martel and Zaras allows the identification of clusters of parameters that respect the preferences of the decision maker. When launching an order for a product, the decision maker may judge certain sets of parameters to be equivalent. A visual interactive simulation model will then allow their comparison according to three performance criteria.