Evolutionary computation techniques have mostly been used to solve various optimization problems, and it is well known that graph isomorphism problem （GIP） is a nondeterministic polynomial problem. A simulated annea...Evolutionary computation techniques have mostly been used to solve various optimization problems, and it is well known that graph isomorphism problem （GIP） is a nondeterministic polynomial problem. A simulated annealing （SA） algorithm for detecting graph isomorphism is proposed, and the proposed SA algorithm is well suited to deal with random graphs with large size. To verify the validity of the proposed SA algorithm, simulations are performed on three pairs of small graphs and four pairs of large random graphs with edge densities 0.5, 0.1, and 0.01, respectively. The simulation results show that the proposed SA algorithm can detect graph isomorphism with a high probability.展开更多
Circles packing problem is an NP-hard problem and is di?cult to solve. In this paper, ahybrid search strategy for circles packing problem is discussed. A way of generating new configurationis presented by simulating t...Circles packing problem is an NP-hard problem and is di?cult to solve. In this paper, ahybrid search strategy for circles packing problem is discussed. A way of generating new configurationis presented by simulating the moving of elastic objects, which can avoid the blindness of simulatedannealing search and make iteration process converge fast. Inspired by the life experiences of people,an e?ective personified strategy to jump out of local minima is given. Based on the simulatedannealing idea and personification strategy, an e?ective personified annealing algorithm for circlespacking problem is developed. Numerical experiments on benchmark problem instances show thatthe proposed algorithm outperforms the best algorithm in the literature.展开更多
基金the National Natural Science Foundation of China (60373089, 60674106, and 60533010)the National High Technology Research and Development "863" Program (2006AA01Z104)
文摘Evolutionary computation techniques have mostly been used to solve various optimization problems, and it is well known that graph isomorphism problem （GIP） is a nondeterministic polynomial problem. A simulated annealing （SA） algorithm for detecting graph isomorphism is proposed, and the proposed SA algorithm is well suited to deal with random graphs with large size. To verify the validity of the proposed SA algorithm, simulations are performed on three pairs of small graphs and four pairs of large random graphs with edge densities 0.5, 0.1, and 0.01, respectively. The simulation results show that the proposed SA algorithm can detect graph isomorphism with a high probability.
文摘Circles packing problem is an NP-hard problem and is di?cult to solve. In this paper, ahybrid search strategy for circles packing problem is discussed. A way of generating new configurationis presented by simulating the moving of elastic objects, which can avoid the blindness of simulatedannealing search and make iteration process converge fast. Inspired by the life experiences of people,an e?ective personified strategy to jump out of local minima is given. Based on the simulatedannealing idea and personification strategy, an e?ective personified annealing algorithm for circlespacking problem is developed. Numerical experiments on benchmark problem instances show thatthe proposed algorithm outperforms the best algorithm in the literature.
基金Supported by the Academician Start-Up Fund of China under Grant No.X01109(厦门大学院士启动基金)the 985 Information Technology Fund of China under Grant No.0000-X07204(985信息科技平台资助)
