Abstract

The issue of production planning and optimization has received a consistent attention from researchers and practitioners for decades, and a number of methodologies for modeling and optimizing production lines have been reported in the research community. Although this is an important issue, there is room for improvement. The majority of existing methodologies assume that processing times are deterministic. From the practical point of view, however, the processing times behave in a random fashion. This paper revisits the traditional part-machine allocation problem and proposes a stochastic programming model where the processing times are described by random variables.

Keywords Allocation, Processing time, Stochastic programming, Chance Constraint Programming, Optimization.