Abstract
A new type of approximate algorithms for optimization problems, called membrane algorithms, is proposed, which can be seen as an application of membrane computing to evolutionary computing. A membrane algorithm consists of several membrane separated regions, where subalgorithms and tentative solutions to the optimization problem to be solved are placed, as well as a solution transporting mechanism between adjacent regions. The subalgorithms improve tentative solutions simultaneously. After that, the best and worst solutions in a region are sent to adjacent inner and outer regions, respectively. By repeating this process, a good solution will appear in the innermost region. The algorithm terminates if a terminate condition is satisfied. A simple condition of this type is the number of iterations, while a little more sophisticated condition becomes true if the good solution is not changed during a predetermined period. Computer experiments show that such algorithms are rather efficient in solving the travelling salesman problem.
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Nishida, T.Y. (2006). Membrane Algorithms. In: Freund, R., Păun, G., Rozenberg, G., Salomaa, A. (eds) Membrane Computing. WMC 2005. Lecture Notes in Computer Science, vol 3850. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11603047_4
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DOI: https://doi.org/10.1007/11603047_4
Publisher Name: Springer, Berlin, Heidelberg
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