Research on Path Optimization Based on Improved Adaptive Genetic Algorithm
XIAO Zi-qian
CHEN Jing-you
WANG Rui-qing
Abstract：Path optimization, which can improve the travel efficiency of vehicles, has significances in time and cost saving. Path optimization mentioned in this article aims for optimizing the total length and converts it into classical TSP to solve optimization problems and establishes path optimization model. Based on this model, the improved adaptive genetic algorithm is put forward. This algorithm improves the populationfitness sorting, adaptive crossover probability and mutation probability, etc. The comparison of simulation experiments shows that the improved adaptive genetic algorithm (AGA) has better global optimization ability and faster convergence speed than Simple Genetic Algorithm (SGA), hence an effective method to promote path optimization.
Keywords：path optimizationgenetic algorithm (GA)TSPadaptive
Publication Date：2016-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：3( 28-30 )