An Approximate Algorithm Combining P Systems and Active Evolutionary Algorithms for Traveling Salesman Problems

  • Xiaoxiao Song School of Electrical and Information Engineering Xihua University, Chengdu, Sichuan, P.R. China, 610039 *Corresponding author:
  • Jun Wang School of Electrical and Information Engineering Xihua University, Chengdu, Sichuan, P.R. China, 610039


An approximate algorithm combining P systems and active evolutionary algorithms (AEAPS) to solve traveling salesman problems (TSPs) is proposed in this paper. The novel algorithm uses the same membrane structure, subalgorithms and transporting mechanisms as Nishida’s algorithm, but adopts two classes of active evolution operators and a good initial solution generating method. Computer experiments show that the AEAPS produces better solutions than Nishida’s shrink membrane algorithm and similar solutions with an approximate optimization algorithm integrating P systems and ant colony optimization techniques (ACOPS) in solving TSPs. But the necessary number of iterations using AEAPS is less than both of them.


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How to Cite
SONG, Xiaoxiao; WANG, Jun. An Approximate Algorithm Combining P Systems and Active Evolutionary Algorithms for Traveling Salesman Problems. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 10, n. 1, p. 89-99, nov. 2014. ISSN 1841-9844. Available at: <>. Date accessed: 30 sep. 2020. doi:


P systems, active evolutionary algorithms, traveling salesman problems