The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
A pesquisa do problema do caminho mais curto em redes dependentes do tempo tem importante valor prático. Foi proposta uma estratégia aprimorada de atualização de feromônios adequada para redes dependentes do tempo. Sob esta estratégia, o feromônio residual de cada estrada pode refletir com precisão a mudança no valor ponderado de cada estrada. Uma estratégia de selecção melhorada entre cidades adjacentes foi utilizada para calcular as probabilidades de transferência das cidades, como resultado, a quantidade de cálculo é bastante reduzida. Para evitar que o algoritmo convergisse para a solução ótima local, o algoritmo de colônia de formigas foi combinado com o algoritmo genético. Desta forma, as soluções após cada percurso foram utilizadas como espécie inicial para realizar o cruzamento de ponto único. Foi apresentado um algoritmo aprimorado de colônia de formigas para o problema do caminho mais curto em redes dependentes do tempo, baseado nessas estratégias aprimoradas. Os resultados da simulação mostram que o algoritmo aprimorado tem maior probabilidade de obter a solução ideal global e a taxa de convergência do algoritmo é melhor do que o algoritmo tradicional de colônia de formigas.
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Qing CHANG, Yongqiang LIU, Huagang XIONG, "An Improved Ant Colony Algorithm for the Shortest Path Problem in Time-Dependent Networks" in IEICE TRANSACTIONS on Communications,
vol. E92-B, no. 9, pp. 2996-2999, September 2009, doi: 10.1587/transcom.E92.B.2996.
Abstract: Research of the shortest path problem in time-dependent networks has important practical value. An improved pheromone update strategy suitable for time-dependent networks was proposed. Under this strategy, the residual pheromone of each road can accurately reflect the change of weighted value of each road. An improved selection strategy between adjacent cities was used to compute the cities' transfer probabilities, as a result, the amount of calculation is greatly reduced. To avoid the algorithm converging to the local optimal solution, the ant colony algorithm was combined with genetic algorithm. In this way, the solutions after each traversal were used as the initial species to carry out single-point crossover. An improved ant colony algorithm for the shortest path problem in time-dependent networks based on these improved strategies was presented. The simulation results show that the improved algorithm has greater probability to get the global optimal solution, and the convergence rate of algorithm is better than traditional ant colony algorithm.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E92.B.2996/_p
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@ARTICLE{e92-b_9_2996,
author={Qing CHANG, Yongqiang LIU, Huagang XIONG, },
journal={IEICE TRANSACTIONS on Communications},
title={An Improved Ant Colony Algorithm for the Shortest Path Problem in Time-Dependent Networks},
year={2009},
volume={E92-B},
number={9},
pages={2996-2999},
abstract={Research of the shortest path problem in time-dependent networks has important practical value. An improved pheromone update strategy suitable for time-dependent networks was proposed. Under this strategy, the residual pheromone of each road can accurately reflect the change of weighted value of each road. An improved selection strategy between adjacent cities was used to compute the cities' transfer probabilities, as a result, the amount of calculation is greatly reduced. To avoid the algorithm converging to the local optimal solution, the ant colony algorithm was combined with genetic algorithm. In this way, the solutions after each traversal were used as the initial species to carry out single-point crossover. An improved ant colony algorithm for the shortest path problem in time-dependent networks based on these improved strategies was presented. The simulation results show that the improved algorithm has greater probability to get the global optimal solution, and the convergence rate of algorithm is better than traditional ant colony algorithm.},
keywords={},
doi={10.1587/transcom.E92.B.2996},
ISSN={1745-1345},
month={September},}
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TY - JOUR
TI - An Improved Ant Colony Algorithm for the Shortest Path Problem in Time-Dependent Networks
T2 - IEICE TRANSACTIONS on Communications
SP - 2996
EP - 2999
AU - Qing CHANG
AU - Yongqiang LIU
AU - Huagang XIONG
PY - 2009
DO - 10.1587/transcom.E92.B.2996
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E92-B
IS - 9
JA - IEICE TRANSACTIONS on Communications
Y1 - September 2009
AB - Research of the shortest path problem in time-dependent networks has important practical value. An improved pheromone update strategy suitable for time-dependent networks was proposed. Under this strategy, the residual pheromone of each road can accurately reflect the change of weighted value of each road. An improved selection strategy between adjacent cities was used to compute the cities' transfer probabilities, as a result, the amount of calculation is greatly reduced. To avoid the algorithm converging to the local optimal solution, the ant colony algorithm was combined with genetic algorithm. In this way, the solutions after each traversal were used as the initial species to carry out single-point crossover. An improved ant colony algorithm for the shortest path problem in time-dependent networks based on these improved strategies was presented. The simulation results show that the improved algorithm has greater probability to get the global optimal solution, and the convergence rate of algorithm is better than traditional ant colony algorithm.
ER -