Optimization of drug transportation to pharmacies

This thesis presents an optimization model with an aim of minimi- zing losses in the distribution of drugs to pharmacies. The first part summarizes the basic properties of linear programming with a focus on the transportation problem. The second part describes the basic properties of two-stage stochastic linear programming and formulates a two-stage stochastic linear program with a chance constraint. On that basis, the paper introduces three possible models for drug distribution. The first model is formulated as a linear programming problem. The second model represents a two-stage stochastic linear program, where the pa- per considers the demand of pharmacies as a random element. Consequently, our analysis enriches the model by a chance constraint. The goal of this model is to maximize profits, subject to the condition that each of the pharmacies will serve all customers is greater than or equal to 1 − α. The underlying aim of all three models is to minimize the losses. The ideal solutions of both models, formulated as stochastic linear problems, will be discussed in regards to the output data, and, in the case of the model involving chance constraint to the parameter α, respectively