Optimization of Office Transportation System by using Clustering and Genetic Algorithms

One of the major solutions for sustainable use of resources is official transportation system. Nowadays, the current transportation systems are determined optionally by people opinions, whereas this choice is not optimum. Therefore, a method must be taken due to a model to solve this problem efficiently. On the other hand, if the number of employees is considerable in a company, the problem area will be increased and using the mathematic algorithms will be difficult. Therefore in this paper the authors tried to reduce the problem’s search area by simple clustering method and then searched optimum path for employees in each cluster by population-based Genetic Algorithm. But one of problems about Genetic Algorithm using operations are appropriate for problematic conditions. In this paper the authors tried to develop the problem- solving conditions by using the appropriate cross over and mutation operations and then decrease spend time for finding the optimum solution. This algorithm is used in a part of Tehran city, and the information refers to 2006. By using the developed algorithm, on one hand, problem is responsive and the on the other hand problem is converged to optimum answer with lower repetition number in comparison with genetic method with simple operations and it has high repeatable test. At the end, the authors propose some suggestions to close the problem’s condition to real world condition and using some other population-based algorithms.