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Transportation is a major problem domain in logistics, and so it represents a substantial task in the activities of many companies. In some market sectors, transportation means a high percentage of value added to goods. Therefore, the utilization of computerized methods for transportation often results in significant savings ranging from 5% to 20% in the total costs. For this high complexity problem without any known sophisticated solution technique, a genetic approach is well suited. GA generates solutions to optimization problems using techniques inspired by natural evolution, such as selection, crossover and mutation.