الفهرس 
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Abstract
In production planning companies are looking for better ways to improve the utilization of their resources to growing the competition between them. For that reason the good production plans is the starting point for their success.
Aggregate production planning (APP) is an intermediate range planning, few successful implementations have been recorded. The aggregate production planning is a typical high-level decision making problem with lots of uncertain factors involved. To develop an aggregate production planning complete information must be on hand about available machine capacity, workers availability, and cost related to decision activities.
A lot of real world decisions problems are described by multi objective linear programming models and sometimes its necessary to formulate them with elements of imprecision or uncertainty and they are represented by fuzzy numbers described by their possibility distribution estimated by the analyst from the information supplied by the decision maker (DM)
In the present work, applying possibilistic linear programming (PLP) to real aggregate production planning (APP) problem (paint factory) with multi product and multi period in fuzzy environment. In real-world APP problems the input data such as demand, resources costs are fuzzy in nature. The model tries to minimize the total production cost, allows the decision maker to solve a problem according to the current information, and interactively modify the imprecise data and related model parameters until a satisfactory solution is obtained. . So, it’s suitable for applying APP model. It applies to meet minimum cost for chosen product family under uncertainty in demand. In this work we add cost budget constraint to the applying model as a condition to obtain the DM’s satisfactions. Consequently, the model is the most suitable for making real world APP decisions.