计算机科学 ›› 2018, Vol. 45 ›› Issue (6A): 63-68.
马元锋1,李昂儒2,余慧敏2,潘晓英2,3
MA Yuan-feng1,LI Ang-ru2,YU Hui-min2,PAN Xiao-ying2,3
摘要: 多目标免疫优化算法的研究目标是种群均匀分布于优化问题的非劣最优域并使算法快速收敛。为进一步提高多目标优化问题非支配解集合的分布均匀性和收敛性,提出了一种基于动态拥挤距离的混合多目标免疫优化算法。该算法基于动态拥挤距离来对个体进行比较和更新操作,从而保持最终解集的均匀分布,同时借鉴经典差分进化算法中的变异引导算子来加强免疫优化算法的局部搜索能力并提高搜索精度。基于5个经典测试函数的仿真结果表明,与其他几种有效的多目标优化算法相比,所提算法不仅在求得Pareto最优解集的逼近性、均匀性和宽广性上有明显优势,而且收敛速度也有较大的改进和提高。
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[1]LIN H,PENG Y.Immune clonal algorithm with fitness sharing for multi-objective optimization [J].Control Theory & Applications,2011,28(2):206-214. [2]SHANG R,JIAO L,YU H,et al.Quantum immune clone for solving constrained multi-objective optimization[J].Evolutiona-ry Computation,2015,3(4):26-41. [3]AN S,LI Q,YANG S.An Improved Light Beam Search Method in Multi-objective Inverse Problem Optimizations[J].IEEE Transactions on Magnetics,2016,52(3):1-4. [4]FONSECA C M,FLEMING P J.Genetic algorithm for multi-objective optimization:Formulation,discussion and generation[C]∥5th Int’l Conf.on Genetic Algorithms.San Mateo:Morgan Kauffman Publishers,1993:416-423. [5]SRINIVAS N,DEB K.Multi-objective optimization using non-dominated sorting in genetic algorithms[J].Evolutionary Computation,1994,2(3):221-248. [6]HORN J,NAFPLIOTIS N,GOLDBERG D E.A niched Pareto genetic algorithm for multi-objective optimization[C]∥1st IEEE Congress on Evolutionary Computation.Piscataway:IEEE,1994:82-87. [7]ZITZLER E,LAUMANNS M,THIELE L.SPEA2:Improving the strength Pareto evolutionary algorithm[C]∥Evolutionary Methods for Design,Optimization and Control with Applications to Industrial Problems.Berlin:Springer-Verlag,2002:95-100. [8]KNOWLES J D,CORNE D W.Approximating the non-dominated front using the Pareto archived evolution strategy[J].Evolutionary Computation,2000,8(2):149-172. [9]CORNE D W,JERAM N R,KNOWLES J D,et al.PESA-II:Region-Based selection in evolutionary multi-objective optimization[C]∥Genetic and Evolutionary Computation Conf.(GECCO 2001).San Francisco:Morgan Kaufmann Publishers,2001:283-290. [10]ERICKSON M,MAYER A,HORN J.The niched Pareto gene- tic algorithm 2 applied to the design of groundwater remediation system[C]∥1st Int’l Conf.on Evolutionary Multi-Criterion Optimization(EMO 2001).Berlin:Springer-Verlag,2001:681-695. [11]DEB K,PRATAP A,AGARWAL S,et al.A fast and elitist multi-objective genetic algorithm:NSGA-II[J].IEEE Transactions on Evolutionary Computation,2002,6(2):182-197. [12]MARTINEZ S Z,COELLO C A C.A multi-objective evolutiona- ry algorithm based on decomposition for constrained multi-objective optimization [C]∥2014 IEEE Congress on Evolutionary Computation.Beijing,China:IEEE,2014:429-436. [13]ZHU Q,LIN Q,DU Z,et al. A novel adaptive hybrid crossover operator for multiobjective evolutionary algorithm.Information Sciences,2016,345(C):177-198. [14]QI Y,HOU Z,YIN M,et al.An immune multi-objective optimization algorithm with differential evolution inspired recombination .Applied Soft Computing,2015,29(C):395-410. [15]FRESCHI F,REPETTO M.VIS:An artificial immune network for multi-objective optimization[J].Engineering Optimization,2006,38(8):975-996. [16]JIAO L C,GONG M G,SHANG R H,et al.Clonal selection with Immune dominance and energy based multi-objective optimization[C]∥3rd Int’l Conf.on Evolutionary Multi-Criterion Optimization(EMO 2005).Berlin:Springer-Verlag,2005:474-489. [17]GONG M G,JIAO L C,DU H F,et al.Multi-objective immune algorithm with non-dominated neighbor-based selection[J].Evolutionary Computation,2008,16(2):225-255. [18]舒万能,丁立新,汪慎文.基于反馈机制的克隆反馈优化算法的稳定性研究[J].计算机科学,2012,39(10):187-189. [19]戚玉涛,刘芳,常伟远,等.求解多目标问题的Memetic免疫优化算法[J].软件学报,2013,19(7):1529-1544. [20]公茂果,焦李成,杨咚咚,等.进化多目标优化算法研究[J].软件学报,2009,20(2):271-289. [21]DEB K,PRATAP A,AGARWAL S,et al.A fast and elitist multi-objective genetic algorithm:NSGA-II[J].IEEE Transactions on Evolutionary Computation,2002,6(2):182-197. [22]WANG H,WANG W,SUN H,et al.A new cuckoo search algorithm with hybrid strategies for flow shop scheduling problems[J].Soft Computing,2017,21(15):4297-4307. [23]CASEIRO R,HENRIQUES J F,MARTINS P,et al.A non- parametric Riemannian framework on tensor field with application to foreground segmentation[C]∥IEEE International Conference on Computer Vision.IEEE,2011:1-8. [24]ZHANG H,ZHOU A,SONG S,et al.A Self-Organizing Multi-objective Evolutionary Algorithm.IEEE Transactions on Evolutionary Computation,2016,20(5):792-896. [25]GIAGKIOZIS I,PURSHOUSE R C,FLEMING P J.An overview of population-based algorithms for multi-objective optimization[J].International Journal of Systems Science,2015,46(9):1572-1599. |
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