ZHANG Gexiang, RONG Haina, CHENG Jixiang, QIN Yanhui. A Population-Membrane-System-Inspired Evolutionary Algorithm for Distribution Network Reconfiguration[J]. Chinese Journal of Electronics, 2014, 23(3): 437-441.
Citation: ZHANG Gexiang, RONG Haina, CHENG Jixiang, QIN Yanhui. A Population-Membrane-System-Inspired Evolutionary Algorithm for Distribution Network Reconfiguration[J]. Chinese Journal of Electronics, 2014, 23(3): 437-441.

A Population-Membrane-System-Inspired Evolutionary Algorithm for Distribution Network Reconfiguration

Funds:  This work was supported by the National Natural Science Foundation of China (No.61170016, No.61373047), the Program for New Century Excellent Talents in University (No.NCET-11-0715) and SWJTU supported project (No.SWJTU12CX008).
  • Received Date: 2012-12-01
  • Rev Recd Date: 2013-11-01
  • Publish Date: 2014-07-05
  • This paper proposes a Populationmembrane-system-inspired evolutionary algorithm (PMSIEA), which is designed by using a population P system and a Quantum-inspired evolutionary algorithm (QIEA). PMSIEA uses the population P system with three cells to organize three variants of QIEAs, where communications between cells are performed at the level of genes, instead of the level of individuals reported in the existing membrane algorithms. This work provides a useful framework for synthesizing different algorithms at macro level and exchanging genic information at micro scale. Experimental results conduced on knapsack problems show that PMSIEA is superior to four representative QIEAs and our previous work with respect to the quality of solutions and the elapsed time. We also use PMSIEA to solve the optimal distribution system reconfiguration problem in power systems for minimizing the power loss.
  • loading
  • G.X.Zhang, C.X.Liu, H.N.Rong, "Analyzing radar emitter signals with membrane algorithms". Mathematical and Computer Modelling, Vol.52, No.11-12, pp.1997-2010, 2010.
    G.X.Zhang, M.Gheorghe, C.Z.Wu, "A quantum-inspired evolutionary algorithm based on P systems for knapsack problem", Fundamenta Informaticae, Vol.87, No.1, pp.93-116, 2008.
    J.H.Xiao, X.Y.Zhang, J.Xu, "A membrane evolutionary algorithm for DNA sequence design in DNA computing", Chinese Science Bulletin, Vol.57, No.6, pp.698-706, 2012.
    J.H.Xiao, Y.Jiang, J.J.He, Z.Cheng, "A dynamic membrane evolutionary algorithm for solving DNA sequences design with minimum free energy", MATCH Communications in Mathematical and in Computer Chemistry, Vol.70, No.3, pp.971-986, 2013.
    J.J.He, J.H.Xiao, X.L.Shi, T.Song, "A membrane-inspired algorithm with a memory mechanism for knapsack problems", Journal of Zhejiang University-Science C, Vol.14, No.8, pp.612-622, 2013.
    J.H.Xiao, Y.F.Zhang, Z.Cheng, J.J.He, Y.Y. Niu., "A hybrid membrane evolutionary algorithm for solving constrained optimization problems", Optik, Vol.125, No.2, pp.897-902, 2014.
    G.X.Zhang, Y.Q.Li, M.Gheorghe, "A membrane algorithm with quantum-inspired subalgorithms and its application to image processing", Natural Computing, Vol.11, No.4, pp.701-717, 2012.
    G.X.Zhang, J.X.Cheng, M.Gheorghe, Q.Meng, "A hybrid approach based on differential evolution and tissue membrane systems for solving constrained manufacturing parameter optimization problems", Applied Soft Computing, Vol.13, No.3, pp.1528-1542, 2013.
    G.X.Zhang, "Quantum-inspired evolutionary algorithms: A survey and empirical study", Journal of Heuristics, Vol.17, No.3, pp.303-351, 2011.
    H.L.Xing, Y.F.Ji, L.Bai, X.Liu, "An adaptive-evolution-based quantum genetic algorithm for QoS multicast routing problem", Chinese Journal of Electronics, Vol.18, No.3, pp.525-529, 2009.
    F.Bernardini, M.Gheorghe, "Population P systems", Journal of Universal Computer Science, Vol.10, No.5, pp.509-539, 2004.
    K.H.Han, J.H.Kim, "Quantum-inspired evolutionary algorithm for a class of combinatorial optimization", IEEE Trans. on Evolutionary Computation, Vol.6, No.6, pp.580-593, 2002.
    K.H.Han, J.H.Kim, "Quantum-inspired evolutionary algorithms with a new termination criterion, H gate, and two-phase scheme", IEEE Trans. on Evolutionary Computation, Vol.8, No.2, pp.156-169, 2004.
    R.Zhang, H.Gao, "Improved quantum evolutionary algorithm for combinatorial optimization problem", Proc of Int. Conf. on Machine Learning and Cybernetics, Hong Kong, China, pp.3501-3505, 2007.
    J.Vlachogiannis, K.Lee, "Quantum-inspired evolutionary algorithm for real and reactive power dispatch", IEEE Trans. on Power Systems, Vol.23, No.4, pp.1627-1636, 2008.
    A.Abdelaziz, F.Mohammed, S.Mekhamer, M.Badr, "Distribution systems reconfiguration using a modified particle swarm optimization algorithm", Electric Power Systems Research, Vol.79, No.11, pp.1521-1530 2009.
    J.A.Martín, A.J.Gil, "A new heuristic approach for distribution systems loss reduction", Electric Power Systems Research, Vol.78, No.11, pp.1953-1958, 2008.
    A.Swarnkar, N.Gupta, K.Niazi, "Efficient reconfiguration of distribution systems using ant colony optimization adapted by graph theory", Proc. of Power and Energy Society General Meeting, Detroit, Michigan, USA, pp. 1-8, 2011.
    Y.J.Jeon, J.C.Kim, "Application of simulated annealing and tabu search for loss minimization in distribution systems", International Journal of Electrical Power & Energy Systems, Vol.26, No.1, pp.9-18, 2004.
    S.Mekhamer, A.Abdelaziz, F.Mohammed, M.Badr, "A new intelligent optimization technique for distribution systems reconfiguration", Proc. of Int. Middle-East Power System Conf., Nile Cruise, Aswan, Egypt, pp. 397-401, 2008.
    M.A.Ghorbani, S.H.Hosseinian, B.Vahidi, "Application of ant colony system algorithm to distribution networks reconfiguration for loss reduction", Proc. of Int. Conf. on Optimization of Electrical and Electronic Equipment, Brasov, Romania, pp. 269-273, 2008.
    Z.K.Li, X.Y.Chen, K.Yu, Y.Sun, H.M.Liu, "A hybrid particle swarm optimization approach for distribution network reconfiguration problem", Proc. of Power and Energy Society General Meeting, Pittsburgh, Pennsylvania, USA, pp. 1-7, 2008.
    F.Nournejad, R.Kazemzade, A.S.Yazdankhah, "A multiobjective evolutionary algorithm for distribution system reconfiguration", Proc. of the 16th Conf. on Electrical Power Distribution Networks, Bandar abbas, Iran, pp. 1-7, 2011.
    C.X.Wang, A.J.Zhao, H.Dong, Z.J.Li, "An improved immune genetic algorithm for distribution network reconfiguration", Proc. of Int. Conf. on Information Management, Innovation Management and Industrial Engineering, Xi'an, China, pp.218-223, 2009.
  • 加载中


    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (325) PDF downloads(2003) Cited by()
    Proportional views


    DownLoad:  Full-Size Img  PowerPoint