Considering that the performance of a genetic algorithm （GA） is affected by many factors and their rela-tionships are complex and hard to be described,a novel fuzzy-based adaptive genetic algorithm （FAGA） combined...Considering that the performance of a genetic algorithm （GA） is affected by many factors and their rela-tionships are complex and hard to be described,a novel fuzzy-based adaptive genetic algorithm （FAGA） combined a new artificial immune system with fuzzy system theory is proposed due to the fact fuzzy theory can describe high complex problems.In FAGA,immune theory is used to improve the performance of selection operation.And,crossover probability and mutation probability are adjusted dynamically by fuzzy inferences,which are developed according to the heuristic fuzzy relationship between algorithm performances and control parameters.The experi-ments show that FAGA can efficiently overcome shortcomings of GA,i.e.,premature and slow,and obtain better results than two typical fuzzy GAs.Finally,FAGA was used for the parameters estimation of reaction kinetics model and the satisfactory result was obtained.展开更多
Previous Virtual Network (VN) embedding researches mostly focus on developing heuristic algorithms to enhance the efficiency of a physical resource. However, in the equal-scale condition, where the scale of a VN is si...Previous Virtual Network (VN) embedding researches mostly focus on developing heuristic algorithms to enhance the efficiency of a physical resource. However, in the equal-scale condition, where the scale of a VN is similar to that of a substrate network, the number of successfully mapped VNs decreases sharply since bottlenecks form easily in the substrate network and disturb the embedding process. In this paper, reversed and bidirectional irrigation methods are proposed for the equal-scale and all-scale conditions. The two proposed methods can be combined with most of the existing heuristic algorithms and map a relatively large number of VNs by reducing the potential substrate bottlenecks. The simulation results show that the reversed irrigation method almost doubles the successfully mapped Revenue than the traditional one in the equal-scale condition. Meanwhile, the bidirectional irrigation method achieves the synthetically best performance in almost all scale conditions.展开更多
基金Supported by the National Natural Science Foundation of China（20776042） the National High Technology Research and Development Program of China（2007AA04Z164）+3 种基金 the Doctoral Fund of Ministry of Education of China（20090074110005） the Program for New Century Excellent Talents in University（NCET-09-0346） the＂Shu Guang＂Project（095G29） Shanghai Leading Academic Discipline Project（B504）
文摘Considering that the performance of a genetic algorithm （GA） is affected by many factors and their rela-tionships are complex and hard to be described,a novel fuzzy-based adaptive genetic algorithm （FAGA） combined a new artificial immune system with fuzzy system theory is proposed due to the fact fuzzy theory can describe high complex problems.In FAGA,immune theory is used to improve the performance of selection operation.And,crossover probability and mutation probability are adjusted dynamically by fuzzy inferences,which are developed according to the heuristic fuzzy relationship between algorithm performances and control parameters.The experi-ments show that FAGA can efficiently overcome shortcomings of GA,i.e.,premature and slow,and obtain better results than two typical fuzzy GAs.Finally,FAGA was used for the parameters estimation of reaction kinetics model and the satisfactory result was obtained.
基金supported by the National Basic Research Program of China under Grants No.2012CB315801,No.2011CB302901the National Science and Technology Major Projects under Grant No.2010ZX03004-002-02
文摘Previous Virtual Network (VN) embedding researches mostly focus on developing heuristic algorithms to enhance the efficiency of a physical resource. However, in the equal-scale condition, where the scale of a VN is similar to that of a substrate network, the number of successfully mapped VNs decreases sharply since bottlenecks form easily in the substrate network and disturb the embedding process. In this paper, reversed and bidirectional irrigation methods are proposed for the equal-scale and all-scale conditions. The two proposed methods can be combined with most of the existing heuristic algorithms and map a relatively large number of VNs by reducing the potential substrate bottlenecks. The simulation results show that the reversed irrigation method almost doubles the successfully mapped Revenue than the traditional one in the equal-scale condition. Meanwhile, the bidirectional irrigation method achieves the synthetically best performance in almost all scale conditions.
