Abstract
Aiming at the problem that the traditional path planning method of porter is easy to fall into local optimum solution and lacks general adaptability to the environment, a working environment model of porter is created by using the grid method. Based on an improved greedy algorithm for establishing a search tabu table, the simulated annealing coefficient and the grid coefficient are redefined by adding the idea of “survival of the fittest” in the genetic algorithm. An improved simulated annealing algorithm is proposed to solve the local convergence problem of greedy algorithm. Finally, the feasibility and adaptability of the algorithm to different environments are verified by simulation and practical experiments, which can effectively improve the quality of transportation vehicle path planning.
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Zhang, S., Wu, M., Guo, C. (2020). Research on Vision Navigation Technology of Porter Based on Improved Simulated Annealing Algorithms. In: Abawajy, J., Choo, KK., Islam, R., Xu, Z., Atiquzzaman, M. (eds) International Conference on Applications and Techniques in Cyber Intelligence ATCI 2019. ATCI 2019. Advances in Intelligent Systems and Computing, vol 1017. Springer, Cham. https://doi.org/10.1007/978-3-030-25128-4_79
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DOI: https://doi.org/10.1007/978-3-030-25128-4_79
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