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According to operation environment and the present situation in the scheduling of public traffic vehicle, signal lamp cycle is taken into account the effect of waiting time of passengers in this paper. A bus optimization scheduling model is built, and it can ensure bus company's economic and passengers' benefits at the same time. According to the problem of low efficiency by the refused strategy, a new fitness function is designed by the penalty strategy. Based on the problems of the simple genetic algorithm in premature convergence and easily getting into local optimum and so on, combining quantum computation with genetic algorithm, quantum genetic algorithm which increases the convergence velocity and good global search capacity is put forward in this paper. Research result shows that the algorithm can effectively solve the combining problems of the bus optimization scheduling. [ABSTRACT FROM AUTHOR]

In multi-agent systems, agents form a coalition to compete the task which is the important cooperation in agents. There are some problems such as slow convergence, low stability and poor optimization when the genetic algorithm is used to solve agent coalition for single task. The paper proposes a single task coalition formation tactic based on improved genetic algorithm. The method defines a parameter to measure the diversity of population about genetic algorithm. The individual is selected to crossover according to matching strategy based on this parameter in the potential crossover set. Ineffective crossover operations are decreased greatly and the efficiency of crossover operation is increased. As the traditional mutation operation lacks a certain direction, the paper presents to find gene mutation based on individuals ability to the agent, to improve the searching performance of the algorithm. The comparative experimental results show that the improved algorithm can find out the coalition quickly and efficiently. [ABSTRACT FROM AUTHOR]

With regard to the maximum power transfer problems under power supplies with three frequencies, this paper discusses the design of load parameters with maximum power matching by genetic algorithm. The maximum power absorbed by the matching load is exactly equal to the sum of the corresponding maximum powers of the load produced separately by respective harmonic component in the supply. Firstly, the circuitry of the maximum power matching load is selected, secondly, the power absorbed by load is set to be fitness function, and lastly, genetic algorithm is applied to search the element parameters which satisfy maximum power matching. The computing results are verified by Multisim. Experimental simulation and computation show that ideal results can be obtained to design maximum power matching load by genetic algorithm. [ABSTRACT FROM AUTHOR]

This paper describe a new design method of controling induction motor driver system, and which is a based on the adaptive variable structure. The adaptive variable structure control driver is an optimization methods system model based on the genetic algorithm model. This method is simple and easily applied. Simulation and experimental results show that the adaptive variable structure controller have strong robustness in providing high performance dynamic characteristics with rapid response, high steady precision, small overshoot, and anti-interference. [ABSTRACT FROM AUTHOR]

The safety of air traffic control is an important factor to ensure fight safety, in order to improve the safety of air traffic control system, it is necessary to assess the risk of human error of air traffic control system. A SHEL model was constructed based on the controller' s error evaluation index system. Because the BP neural network algorithm is easy to fall into local minimum, the paper introduces genetic algorithm to optimize neural network weights and threshold to establish a hybrid algorithm. Evaluation showed that comparing with the traditional prediction BP neural network model with GA-BP algorithm is more accurate, feasible and applicable. It provides certain reference for strengthening the construction of aviation safety management system. [ABSTRACT FROM AUTHOR]