Modeling transportation problems using concepts of swarm intelligence and soft computing

Many real-world problems could be formulated in a way to fit the necessary form for discrete optimization. Discrete optimization problems could be solved by numerous different techniques that have appeared through years. Some of the techniques will provide optimal solution(s) to the problem and some of them will give “good enough” solution(s). Fundamental reason for developing techniques capable of producing solutions that are not necessarily optimal is the fact that many of discrete optimization problems are NP-complete. Metaheuristic algorithms are a common name for a set of general purpose techniques developed to provide solution to the problems belonging to discrete optimization. Mostly the techniques are based on natural metaphors. Countless problems in transportation engineering could be formulated as discrete optimization problems.; Recently, researchers started studying the behavior of social insects (ants) in an attempt to use the swarm intelligence concept to develop artificial systems with the ability to search a problem's solution space in a way that is similar to the foraging search by a colony of social insects. The development of artificial systems does not entail the complete imitation of natural systems, but explores them in search of ideas for modeling. This research is partially devoted to the development of a new system based on foraging behavior of bee colonies - Bee System. The Bee System was tested through many instances of the Traveling Salesman Problem.; Many transportation-engineering problems besides being of combinatorial nature are characterized by uncertainty. In order to treat these problems, the second part of the research is devoted to development of the algorithms combining existing results in the area of swarm intelligence (existing Ant System) and approximate reasoning. The proposed approach—Fuzzy Ant System is tested on the following two examples: Stochastic Vehicle Routing Problem and Schedule Synchronization in Public Transit.