diario americano de Administración de Medicamentos y Terapéutica Acceso abierto

Abstracto

Optimization of energy consumption in land leveling using GIS, genetic and pso (particle swarm optimization) algorithms

Isham Alzoub

One of the most important steps to prepare soil is land leveling. Land leveling with machines require considerable energy.  To increase the accuracy of the calculations, the point height collected from mapping (50 m × 50 m) insert into the GIS environment. rest of the unknown coordinates were obtained using interpolation and a triangular network model (TIN) was used to determine the exact volume of earthworks. In all methods, the equation of the leveling plate, excavation and embankment volumes and maps of land surface after leveling, separation of excavation and embankment and the energy consumption including power of the machine, fuel and manpower were calculated then different methods were compared. The results showed that the ratio of excavation to embankment based on the methods of minimum least squares, genetic algorithm, linear algorithm for optimizing of the particle motions, the particle motion curve algorithm are equal to 1.26, 1.14, 1.12, and 1.16, respectively. On the other hands, the results showed that the method of the particle motion curve algorithm has been shown a 45% reduction in energy consumption in the leveling operation relative to the method of minimum least squares. The genetic algorithm can reduce energy consumption by 42 percent. Between the models used in the method of genetic algorithm, model No. 1 has been estimated that the largest portion of energy consumption is relevant to the fuel (up to 71.83 percent) and the lowest portion of energy consumption is relevant to the manpower (up to 0.38 percent). Therefore, the present study recommends the model of plate-curve genetic algorithm as the best  model.