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Power Line Communications Networking Method Based on Hybrid Ant Colony and Genetic Algorithm
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作者 Qianghui Xiao Huan Jin Xueyi Zhang 《Engineering(科研)》 2020年第8期581-590,共10页
When solving the routing problem with traditional ant colony algorithm, there is scarce in initialize pheromone and a slow convergence and stagnation for the complex network topology and the time-varying characteristi... When solving the routing problem with traditional ant colony algorithm, there is scarce in initialize pheromone and a slow convergence and stagnation for the complex network topology and the time-varying characteristics of channel in power line carrier communication of low voltage distribution grid. The algorithm is easy to fall into premature and local optimization. Proposed an automatic network algorithm based on improved transmission delay and the load factor as the evaluation factors. With the requirements of QoS, a logical topology of power line communication network is established. By the experiment of MATLAB simulation, verify that the improved Dynamic hybrid ant colony genetic algorithm (DH_ACGA) algorithm has improved the communication performance, which solved the QoS routing problems of power communication to some extent. 展开更多
关键词 Power Line Carrier Communication Network Quality of Service hybrid ant colony and genetic Algorithm
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Research on a Task Planning Method for Multi-Ship Cooperative Driving 被引量:4
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作者 CHEN Yaojie XIANG Shanshan CHEN Feixiang 《Journal of Shanghai Jiaotong university(Science)》 EI 2019年第2期233-242,共10页
A new method for a cooperative multi-task allocation problem(CMTAP) is proposed in this paper,taking into account the multi-ship, multi-target, multi-task and multi-constraint characteristics in a multi-ship cooperati... A new method for a cooperative multi-task allocation problem(CMTAP) is proposed in this paper,taking into account the multi-ship, multi-target, multi-task and multi-constraint characteristics in a multi-ship cooperative driving(MCD) system. On the basis of the general CMTAP model, an MCD task assignment model is established. Furthermore, a genetic ant colony hybrid algorithm(GACHA) is proposed for this model using constraints, including timing constraints, multi-ship collaboration constraints and ship capacity constraints. This algorithm uses a genetic algorithm(GA) based on a task sequence, while the crossover and mutation operators are based on similar tasks. In order to reduce the dependence of the GA on the initial population, an ant colony algorithm(ACA) is used to produce the initial population. In order to meet the environmental constraints of ship navigation, the results of the task allocation and path planning are combined to generate an MCD task planning scheme. The results of a simulated experiment using simulated data show that the proposed method can make the assignment more optimized on the basis of satisfying the task assignment constraints and the ship navigation environment constraints. Moreover, the experimental results using real data also indicate that the proposed method can find the optimal solution rapidly, and thus improve the task allocation efficiency. 展开更多
关键词 multi-ship cooperative task allocation path planning MULTI-TASK MULTI-OBJECTIVE genetic ant colony hybrid algorithm(GACHA)
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