Abstract
We propose a new fuzzy mathematical programming model for production planning under uncertainty in an industrial environment. This model considers fuzzy constraints related to the total costs, the market demand and the available capacity of the productive resources and fuzzy coefficients for the costs due to the backlog of demand and for the required capacity. The main goal is to determine the master production schedule of each product, the MRP (Material Requirement Planning) for each raw component in each period, stock levels, demand backlog, and capacity usage levels over a given planning horizon. Finally, the proposed model is tested by using data from an automobile seat assembler and compared with other fuzzy mathematical programming approaches. The experiment shows that the proposed model has not got a better behaviour than more simple fuzzy models, but the advantage is that both types of uncertainties, fuzziness and lack of knowledge or epistemic uncertainty can be considered in a model with fuzzy constraints and fuzzy coefficients.
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