Truck-Shovel fleet, as the most common transportation system in open-pit mines, has a significant part of mining costs, for which an optimal management can lead to a substantial cost reduction. Among the available dispatch MATHEMATICAL MODELs, a multi-stage approach is well-suited for allocating trucks to the respected shovels in a dynamic dispatching program. However, with this kind of MODELing, sequencing the allocated trucks is not possible, though it is important to find out the best solution to get the minimum cost. To comply with the shortcoming of the traditional MODEL, in this work, a new hybrid MODEL is developed and applied to the Sungon Copper Mine in Iran, in which, for each truck, an allocation matrix is considered as the input to the genetic algorithm implemented to determine the best solution. According to the results obtained, the optimal sequencing of the trucks can result in a significant (31%) cost reduction in a shift.