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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.

- Publication
- IEICE TRANSACTIONS on Communications Vol.E92-B No.9 pp.2996-2999

- Publication Date
- 2009/09/01

- Publicized

- Online ISSN
- 1745-1345

- DOI
- 10.1587/transcom.E92.B.2996

- Type of Manuscript
- LETTER

- Category
- Integrated Systems for Communications

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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 -