Otimização sob restrições probabilísticas: teoria e aplicações

Abstract

This Project brings a Chance Constrained Programming substantial approaching (CCP). This kind of optimization is used to pattern uncertainties and became useful to all kind of knowledge areas. The project main idea was to show CCP s theories and beyond this to present some applications on Engineering and Public Politics areas. It is noteworthy to say that this tool is pretty important for the production systems because of its uncertainties process. So after showing the theory whose purpose is to comprehend the Chance Constrained Programming, this subject commits itself to apply such technique in Emergency Medical Care Production Services (SAMU) in João Pessoa using the proposed model from Beraldi et al. (2004). This application was really useful to define the necessary ambulances to supply João Pessoa s city as well as the local they must be. However, to understand this technique and also work with it it s necessary a previous knowledge of Statistics, Applied Mathematics and Computing. Therefore, this work emphasizes the continuous and discreet random variables, as well as the probabilistic functions and concepts. In Applied Mathematics, this work brings a Linear Optimization, Facility Location and log concave functions. Concerning to computing, it was used MATLAB R007, Google Maps and CPLEX to provide the model. The great benefit of using CCP is that it offers possible solutions to the person who chooses between them, according to the reality.