In order to solve the constraint satisfied problem in the genetic algorithm, the partheno-genetic algorithm is designed. And then the schema theorem of the partheno-genetic algorithm is proposed to show that the high ...In order to solve the constraint satisfied problem in the genetic algorithm, the partheno-genetic algorithm is designed. And then the schema theorem of the partheno-genetic algorithm is proposed to show that the high rank schemas at the subsequent generation decrease exponentially even though its fitness is more optimal than the average one in the population and the low rank schemas at the subsequent generation increase exponentially when its fitness is more optimal than the average one in the population. In order to overcome the shortcoming that the optimal high rank schema can be deserted arbitrarily, the HGA (hybrid partheno-genetic algorithm) is proposed, that is, the hill-climbing algorithm is integrated to search for a better individual. Finally, the results of the simulation for facility layout problem and no-wait schedule problem are given. It is shown that the hybrid partheno- genetic algorithm is of high efficiency.展开更多
In this paper, a kind of Partheno Genetic Algorithm(PGA)based on Path Representation scheme is pro-posed for solving Traveling Salesman Problem(TSP). This algorithm employs only mutation and selection operatorsto prod...In this paper, a kind of Partheno Genetic Algorithm(PGA)based on Path Representation scheme is pro-posed for solving Traveling Salesman Problem(TSP). This algorithm employs only mutation and selection operatorsto produce the offspring, instead of traditional crossover operator. A specific mutation operator is designed combiningthe insertion operator with inversion operator, which ensures its strong searching capability. This algorithm simu-lates the recurrence of nature evolution process, while providing fewer control parameters. Experiments based onChinese 144 cities(CHN144)and 7 instances selected from TSPLIB are used to test the performance of this algorithm.They prove that it can reach the satisfying optimization at a faster speed. Especially, for the CHN144, the best pathit finds is better than any other available one.展开更多
针对电动汽车充电站选址定容的配电网规划问题,建立了以配电网投资及运行成本、电动汽车充电站投资及运行成本最小为优化目标的模型。采用带精英策略的改进树形结构编码单亲遗传算法ITSE-PGA(improved tree structure encoding partheno...针对电动汽车充电站选址定容的配电网规划问题,建立了以配电网投资及运行成本、电动汽车充电站投资及运行成本最小为优化目标的模型。采用带精英策略的改进树形结构编码单亲遗传算法ITSE-PGA(improved tree structure encoding partheno-genetic algorithm),在配电网规划的同时进行了电动汽车充电站位置和容量的优化。不同于用于传统的配电网规划的树形结构编码单亲遗传算法,该方法在含电动汽车充电站的优化过程中,配电网络不一定连通,所以要对不可行解做特殊处理。通过算例仿真,验证了该方法的可行性和有效性。展开更多
In this paper, a kind of Partheno Genetic Algorithm (PGA) based on Path Representation scheme is proposed for solving Traveling Salesman Problem (TSP). This algorithm employs only mutation and selection operators to p...In this paper, a kind of Partheno Genetic Algorithm (PGA) based on Path Representation scheme is proposed for solving Traveling Salesman Problem (TSP). This algorithm employs only mutation and selection operators to produce the offspring,instead of traditional crossover operator. A specfiic mutation operator is designed combining the insertion operator with reversion operator,which ensures its strong searching capability. This algorithm simulates the recurrence of nature evolution process, while providing fewer control parameters. Experiments based on Ciunese 144 cities(CHN144)and 7 instances selected from TSPLIB are used to test the performance of this algorithm. They prove that it can reach the satisfying optimization at a faster speed. Especially,for the CHN144,the best path it finds is better than any other available one.展开更多
文摘In order to solve the constraint satisfied problem in the genetic algorithm, the partheno-genetic algorithm is designed. And then the schema theorem of the partheno-genetic algorithm is proposed to show that the high rank schemas at the subsequent generation decrease exponentially even though its fitness is more optimal than the average one in the population and the low rank schemas at the subsequent generation increase exponentially when its fitness is more optimal than the average one in the population. In order to overcome the shortcoming that the optimal high rank schema can be deserted arbitrarily, the HGA (hybrid partheno-genetic algorithm) is proposed, that is, the hill-climbing algorithm is integrated to search for a better individual. Finally, the results of the simulation for facility layout problem and no-wait schedule problem are given. It is shown that the hybrid partheno- genetic algorithm is of high efficiency.
文摘In this paper, a kind of Partheno Genetic Algorithm(PGA)based on Path Representation scheme is pro-posed for solving Traveling Salesman Problem(TSP). This algorithm employs only mutation and selection operatorsto produce the offspring, instead of traditional crossover operator. A specific mutation operator is designed combiningthe insertion operator with inversion operator, which ensures its strong searching capability. This algorithm simu-lates the recurrence of nature evolution process, while providing fewer control parameters. Experiments based onChinese 144 cities(CHN144)and 7 instances selected from TSPLIB are used to test the performance of this algorithm.They prove that it can reach the satisfying optimization at a faster speed. Especially, for the CHN144, the best pathit finds is better than any other available one.
文摘In this paper, a kind of Partheno Genetic Algorithm (PGA) based on Path Representation scheme is proposed for solving Traveling Salesman Problem (TSP). This algorithm employs only mutation and selection operators to produce the offspring,instead of traditional crossover operator. A specfiic mutation operator is designed combining the insertion operator with reversion operator,which ensures its strong searching capability. This algorithm simulates the recurrence of nature evolution process, while providing fewer control parameters. Experiments based on Ciunese 144 cities(CHN144)and 7 instances selected from TSPLIB are used to test the performance of this algorithm. They prove that it can reach the satisfying optimization at a faster speed. Especially,for the CHN144,the best path it finds is better than any other available one.
