ABSTRACT
Hierarchical production planning is a widely utilized methodology for real-world production planning systems, with the aim to establish alternative decision-making levels of these planning issues. Production can be defined as the process of transforming raw materials into finished products. Effective management of production process ought to provide finished products in appropriate quantities, at the desired times, of the required quality, and at a reasonable cost. Optimization is a methodology relevant to advanced analytical methods for decision making; and is commonly applied with deterministic optimization models, such as those provided through linear, nonlinear, or integer programming. The aggregate production planning problem is one of the biggest problems when making midterm decisions in the operations management of complex manufacturing systems. A stochastic program is usually much more difficult to solve than a deterministic model obtained by simply replacing the random variables with their expected value, or by a particular scenario realization, such as the worst case or most probable scenario.
