Saerens, MarcoCourtain, SylvainVisée, WilliamWilliamVisée2025-05-142025-05-142025-05-142021https://hdl.handle.net/2078.2/24405The societies of today are ruled to produce optimized procedures to be competitive. There is always a moment of need to optimize flow problems inside or outside the company. It can be of several sorts like the transportation of goods from factories to shops or the scheduling of workers to tasks. A panel of algorithms has been developed to solve these problems and always gives the optimal solution. Then, new algorithms based on the bag-of-paths framework have been developed with a new solution property. Instead of having an optimal result, the output is more or less randomized depending on the degree of randomness that is wanted. It is interesting in many sectors like ecology to predict geographic animal behavior. This master thesis consists of the comparison of standard optimal flow algorithms and new algorithms developed in the bag-of-paths framework.constrainted bag-of-pathsrandomized shortest paths with capacity constraintstime comparisonlinear programmingflow problemsA comparison of randomized optimal flow algorithms versus standard optimal flow algorithmstext::thesis::master thesisthesis:31237