The intelligent optimization of a multi-objective evolutionary algorithm is combined with a gradient algorithm. The hybrid multi-objective gradient algorithm is framed by the real number. Test functions are used to analyze the efficiency of the algorithm. In the simulation case of the water phantom, the algorithm is applied to an inverse planning process of intensity modulated radiation treatment （IMRT）. The objective functions of planning target volume （PTV） and normal tissue （NT） are based on the average dose distribution. The obtained intensity profile shows that the hybrid multi-objective gradient algorithm saves the computational time and has good accuracy, thus meeting the requirements of practical applications.
Intensity modulated radiation therapy （IMRT） requires the determination of the appropriate multileaf collimator settings to deliver an intensity map. The purpose of this work was to attempt to regulate the shape between adjacent multileaf collimator apertures by a leaf sequencing algorithm. To qualify and validate this algorithm, the integral test for the segment of the multileaf collimator of ARTS was performed with clinical intensity map experiments. By comparisons and analyses of the total number of monitor units and number of segments with benchmark results, the proposed algorithm performed well while the segment shape constraint produced segments with more compact shapes when delivering the planned intensity maps, which may help to reduce the multileaf collimator＇s specific effects.
