|   [1] Back T, Hammel U, Schwefel H P. Evolutionary computation: Comments on the history and current state. IEEE Transactions on Evolutionary Computation, 1997, 1(1): 3–17 
 
[2] Wolpert D H, Macready W G. No free lunch theorems for optimization. IEEE Transactions on Evolutionary Computation, 1997, 1(1): 67–82 
 
[3] P?aun G. Computing with membranes. Journal of Computer and System Sciences, 2000, 61(1):108–143 
(first circulated at TUCS Research Report No. 208, November 1998) 
 
[4] Mart´?n-Vide C, Pazos J, P?aun G, et al.. Tissue P systems. Theoretical Computer Science, 2003, 296(2): 295–326 
 
[5] Ionescu M, P?aun G, Yokomori T. Spiking neural P systems. Fundamenta Informaticae, 2006, 71(2/3): 279–308 
 
[6] P?aun G, Suzuki Y, Tanaka H, et al.. On the power of membrane division in P systems. Theoretical Computer Science, 2004, 324(1): 61–85 
 
[7] Pan L, P?aun G. Spiking neural P systems with anti-spikes. International Journal of Computers, Commu-nications & Control, 2009, 4(3): 273–282 
 
[8] Song T, Jiang Y, Shi X, et al.. Small universal spiking neural P systems with anti-spikes. Journal of Computational and Theoretical Nanoscience, 2013, 10(4): 999–1006 
 
[9] Pan L, Wang J, Hoogeboom H. Spiking neural P systems with astrocytes. Neural Computation, 2012, 24(3): 805–825 
 
[10] Jiang K, Song T, ChenW, et al.. Homogeneous spiking neural P systems working in sequential mode induced 
by maximum spike number. International Journal of Computer Mathematics, 2013, 90(4): 831–844 
 
[11] Song T, Pan L, P?aun G. Asynchronous spiking neural P systems with local synchronization. Information Sciences, 2013, 219: 197–207 
 
[12] Krishna S, Rama R. A variant of P systems with active membranes: solving NP-complete problems. Romanian Journal of Information Science and Technology, 1999, 2(4): 357–367 
 
[13] Song T, Mac´?as-Ramos L F, Pan L, et al.. Time-free solution to SAT problem using P systems with active 
membranes. Theoretical Computer Science, 2013 [DOI:10.1016/j.tcs.2013.11.014] 
 
[14] He J, Miao Z, Zhang Z, et al.. Solving multidimensional 0-1 knapsack problem by tissue P systems with cell division. Bio-Inspired Computing, 2009. BIC-TA’09. Fourth International Conference on IEEE, 2009: 1–5 
[15] Pan L, P?aun G, P´erez-Jim´enez M J. Spiking neural P systems with neuron division and budding. Science 
China Information Sciences, 2011, 54(8): 1596–1607 
 
[16] Nishida T. An application of P-system: a new algorithm for NP-Complete optimization problem//Proc 8th World Multi-Conference on Systemics, Cybernetics and Informatics, 2004: 109–112 
 
[17] Liang H, Xiongxiong H, Ning W, et al.. P systems based multi-objective optimization algorithm. Progress in Natural Science, 2007, 17(4): 458–465 
 
[18] Cheng J, Zhang G, Zeng X. A Novel Membrane Algorithm Based on Differential Evolution for Numerical Optimization. International Journal of Unconventional Computing, 2011, 7(3): 159–183 
 
[19] Zhang G, Zhou F, Huang X, et al.. A novel membrane algorithm based on particle swarm optimization for solving broadcasting problem. Journal of Universal Computer Science, 2012, 18(13): 1821–1841 
 
[20] Zhang G, Gheorghe M,Wu C. A quantum-inspired evolutionary algorithm based on P systems for knapsack problem. Fundamenta Informaticae, 2008, 87(1): 93–116 
 
[21] Zhang G, Cheng J, Marian G, et al.. A hybrid approach based on differential evolution and tissue membrane systems for solving constrained manufacturing parameter optimization problems. Applied Soft Computing, 2013, 13(3): 1528–1542 
 
[22] Xiao J, Huang Y, Cheng Z, et al.. A hybrid membrane evolutionary algorithm for solving constrained optimization problems. Optik-International Journal for Light and Electron Optics, 2014, 125(2): 897–902 
 
[23] Zhang G, Liu C, Rong H. Analyzing radar emitter signals with membrane algorithms. Mathematical and Computer Modelling, 2010, 52(11): 1997–2010 
 
[24] Xiao J, Zhang X, Xu J. A membrane evolutionary algorithm for DNA sequence design in DNA computing. Chinese Science Bulletin, 2012, 57(6): 698–706 
 
[25] Xiao J, Jiang Y, He J, et al.. A dynamic membrane evolutionary algorithm for solving DNA sequences design with minimum free energy. 2013, 70(3): 971–986 
 
[26] He J, Song T. A Bio-inspired algorithm for the fleet size and mix vehicle routing problem. Journal of Computational and Theoretical Nanoscience (In press) 
 
[27] Zhang G. Quantum-inspired evolutionary algorithms: a survey and empirical study. Journal of Heuristics, 2011, 17(3): 303–351 
 
[28] Cheng J, Zhang G, Ferrante Neri. Enhancing distributed differential evolution with multicultural migration for global numerical optimization. Information Sciences, 2013, 247: 72–93 
 
[29] Leporati A, Pagani D. A Membrane Algorithm for the Min Storage Problem. Membrane Computing. Berlin, Heidelberg: Springer, 2006: 443–462 
 
[30] He J, Xiao J, Shi X, et al.. A membrane-inspired algorithm with a memory mechanism for knapsack problems. Journal of Zhejiang University: Science C, Computers & Electronics, 2013, 14(8): 612–622 
 
[31] Maekawa K, Mori N, Tamaki H, et al.. A genetic solution for the traveling salesman problem by means of a thermodynamical selection rule. Proceedings of IEEE International Conference on Evolutionary Compu-tation, 1996: 529–534 
 
[32] Yoneda M. URL http://www.mikilab.doshisha.ac.jp/dia/research/person/yoneda/research/2002 7 10/SA/ 
07-sareslut.html 
 
[33] Tanaka T, Matsuda S, Furuya T, et al.. Performance comparisons of two Hopfield neural networks for large-scale travelling salesman problems. NASA, 1997(19990036336): 54–55 
 
[34] Tomassini G. TSPLIB. URL http://www.iwr.uni-heidelberg.de/groups/comopt/softwar/TSPLIB95/ 
 
[35] P?aun G. Membrane Computing: An Introduction. Springer, 2002 
 
[36] Prins C. A simple and effective evolutionary algorithm for the vehicle routing problem. Computers & Operations Research, 2004, 31(12): 1985–2002 
 
[37] Baker B M, Ayechew M A. A genetic algorithm for the vehicle routing problem. Computers & Operations Research, 2003, 30(5): 787–800 
 
[38] O´Kelly M E. A quadratic integer program for the location of interacting hub facilities. European Journal of Operational Research, 1987, 32(3): 393–404 
 
[39] Yang J, Zhang R, Liu M. Construction of optimal blocking schemes for robust parameter designs. Acta Mathematica Scientia, 2013, 33B(5): 1431–1438 
 
[40] Sahebi H R, Razani A. A solution of a general equilibrium problem. Acta Mathematica Scientia, 2013, 33B(6): 1598–1614 
 
[41] Xu R, Ding Y. Global solutions and finite time blow up for damped Klein-Gordon equation. Acta Mathe-matica Scientia, 2013, 33B(3): 643–652  |