Membrane algorithms （MAs）, which inherit from P systems, constitute a new parallel and distribute framework for approximate computation. In the paper, a membrane algorithm is proposed with the improvement that the i...Membrane algorithms （MAs）, which inherit from P systems, constitute a new parallel and distribute framework for approximate computation. In the paper, a membrane algorithm is proposed with the improvement that the involved parameters can be adaptively chosen. In the algorithm, some membranes can evolve dynamically during the computing process to specify the values of the requested parameters. The new algorithm is tested on a well-known combinatorial optimization problem, the travelling salesman problem. The em-pirical evidence suggests that the proposed approach is efficient and reliable when dealing with 11 benchmark instances, particularly obtaining the best of the known solutions in eight instances. Compared with the genetic algorithm, simulated annealing algorithm, neural net-work and a fine-tuned non-adaptive membrane algorithm, our algorithm performs better than them. In practice, to design the airline network that minimize the total routing cost on the CAB data with twenty-five US cities, we can quickly obtain high quality solutions using our algorithm.展开更多
DNA sequence design has a crucial role in successful DNA computation,which has been proved to be an NP-hard(non-deterministic polynomial-time hard) problem.In this paper,a membrane evolutionary algorithm is proposed f...DNA sequence design has a crucial role in successful DNA computation,which has been proved to be an NP-hard(non-deterministic polynomial-time hard) problem.In this paper,a membrane evolutionary algorithm is proposed for the DNA sequence design problem.The results of computer experiments are reported,in which the new algorithm is validated and out-performs certain known evolutionary algorithms for the DNA sequence design problem.展开更多
基金supported by the National Natural Science Foundation of China(60903105,61373066,61309015,61033003 and 61320106005)
文摘Membrane algorithms （MAs）, which inherit from P systems, constitute a new parallel and distribute framework for approximate computation. In the paper, a membrane algorithm is proposed with the improvement that the involved parameters can be adaptively chosen. In the algorithm, some membranes can evolve dynamically during the computing process to specify the values of the requested parameters. The new algorithm is tested on a well-known combinatorial optimization problem, the travelling salesman problem. The em-pirical evidence suggests that the proposed approach is efficient and reliable when dealing with 11 benchmark instances, particularly obtaining the best of the known solutions in eight instances. Compared with the genetic algorithm, simulated annealing algorithm, neural net-work and a fine-tuned non-adaptive membrane algorithm, our algorithm performs better than them. In practice, to design the airline network that minimize the total routing cost on the CAB data with twenty-five US cities, we can quickly obtain high quality solutions using our algorithm.
基金supported by the National Natural Science Foundation of China (60903105 and 61003038)the 2008 Program Project of Humanity and Social Science of Nankai University (NKQ08058)+1 种基金the Opening Foundation of the Key Laboratory of the University of Science and Technology of China for High-Performance Computing and Applications (NHPCC-KF-1102)the Scientific Research Foundation for Doctor of AnhuiUniversity (02203104)
文摘DNA sequence design has a crucial role in successful DNA computation,which has been proved to be an NP-hard(non-deterministic polynomial-time hard) problem.In this paper,a membrane evolutionary algorithm is proposed for the DNA sequence design problem.The results of computer experiments are reported,in which the new algorithm is validated and out-performs certain known evolutionary algorithms for the DNA sequence design problem.
