Yizhi Liu1,2, Rutian Qing1,2,*, Liangran Wu1,2, Min Liu1,2, Zhuhua Liao1,2, Yijiang Zhao1,2
Journal on Artificial Intelligence, Vol.3, No.1, pp. 33-43, 2021, DOI:10.32604/jai.2021.016565
- 02 April 2021
Abstract In the large-scale logistics distribution of single logistic center, the
method based on traditional genetic algorithm is slow in evolution and easy to
fall into the local optimal solution. Addressing at this issue, we propose a novel
approach of exploring hybrid genetic algorithm based large-scale logistic
distribution for BBG supermarket. We integrate greedy algorithm and hillclimbing algorithm into genetic algorithm. Greedy algorithm is applied to
initialize the population, and then hill-climbing algorithm is used to optimize
individuals in each generation after selection, crossover and mutation. Our
approach is evaluated on the dataset of BBG Supermarket More >
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