The dynamic capacitated location allocation problem in the military supportive network（DCLAP-MSN） is a representative of combinative optimization problems,and its optimization process is complicated.For this reason,...The dynamic capacitated location allocation problem in the military supportive network（DCLAP-MSN） is a representative of combinative optimization problems,and its optimization process is complicated.For this reason,a dynamic capacitated location allocation model is provided firstly.Then,a hybrid heuristic algorithm which combines genetic algorithm,repair algorithm of solutions and greedy search,is proposed as the solving method.The optimization performance is improved by effectively integrating the repair algorithm of solutions and greedy search with genetic optimization.The experiment results indicate that the proposed algorithm is a feasible and effective method for the problem.展开更多
A dynamic genetic algorithms based on numeric encoding is proposed and its application in system identification is discussed. Simulation shows that the introduction of both numeric encoding and dynamic mutation can ef...A dynamic genetic algorithms based on numeric encoding is proposed and its application in system identification is discussed. Simulation shows that the introduction of both numeric encoding and dynamic mutation can effectively improve the accuracy and speed of searching for the optimum. It also show that the improved Genetic algorithm can identify time delay and parameters of the plant at the same time and converge to globle optimization.展开更多
基金supported by the National Natural Science Foundation of China (70971132)the Elite Plan Program of National University of Defense Technology
文摘The dynamic capacitated location allocation problem in the military supportive network（DCLAP-MSN） is a representative of combinative optimization problems,and its optimization process is complicated.For this reason,a dynamic capacitated location allocation model is provided firstly.Then,a hybrid heuristic algorithm which combines genetic algorithm,repair algorithm of solutions and greedy search,is proposed as the solving method.The optimization performance is improved by effectively integrating the repair algorithm of solutions and greedy search with genetic optimization.The experiment results indicate that the proposed algorithm is a feasible and effective method for the problem.
文摘A dynamic genetic algorithms based on numeric encoding is proposed and its application in system identification is discussed. Simulation shows that the introduction of both numeric encoding and dynamic mutation can effectively improve the accuracy and speed of searching for the optimum. It also show that the improved Genetic algorithm can identify time delay and parameters of the plant at the same time and converge to globle optimization.
