Abstract

The traditional genetic algorithm randomly selects nodes in two chromosomes for crossover operation, which may result in individuals of disconnected or loop circuit and lead to issues as meaningless crossover operations. In order to increase the diversity of the population and prevent the occurrence of premature mutation algorithm which might cause local convergence, this essay presents a new food logistic optimal path planning method. Initialized from the improvement of population genetic algorithm, it designs the fitness function and optimizes crossover and mutation operators so that the optimal or near-optimal solution can be quickly figured out. Moreover, the Matlab software simulation test exhibits the feasibility and effectiveness of the method.

Keywords:

Food logistic, genetic algorithm, path planning,

References