Computer Science ›› 2021, Vol. 48 ›› Issue (4): 1-13.doi: 10.11896/jsjkx.200600151
• Computer Science Theory • Previous Articles Next Articles
LI Li, LI Guang-peng, CHANG Liang, GU Tian-long
CLC Number:
[1]MICHALEWICZ Z S M.Evolutionary algorithms for constrained parameter optimization problems[J].Evolutionary Computation,2014,4(1):1-32. [2]COELLO C A C.Theoretical and numerical constraint-handling techniques used with evolutionary algorithms:a survey of the state of the art[J].Computer Methods in Applied Mechanics and Engineering,2002,191(11/12):1245-1287. [3]DEB K.An efficient constraint handling method for genetic algorithms[J].Computer Methods in Applied Mechanics and Engineering,2000,186(2):311-338. [4]WANG Y,CAI Z X,ZHOU Y R,et al.Constrained optimization evolutionary algorithm [J].Acta Software Sinica,2009,20(1):11-29. [5]DEB K,PRATAP A,AGARWAL S,et al.A fast and elitistmultiobjective genetic algorithm:NSGA-II[J].IEEE Transactions on Evolutionary Computation,2002,6(2):182-197. [6]CUI C G,LI Y J,WU T J.A relative feasibility degree based approach for constrained optimization problems[J].Journal of Zhejiang University-Science C(Computer & Electronics),2010,11(4):249-260. [7]CHENG R,JIN Y,OLHOFER M,et al.A Reference VectorGuided Evolutionary Algorithm for Many-Objective Optimization[J].IEEE Transactions on Evolutionary Computation,2016,20(5):773-791. [8]FAN Z,LI W,CAI X,et al.Angle-based constrained dominance principle in MOEA/D for constrained multi-objective optimization problems[C]//Congress on Evolutionary Computation.2016:460-467. [9]GORDIAN-RIVERA L,MEZURA-MONTES E.A Combination of Specialized Differential Evolution Variants for Constrained Optimization[C]//Ibero-American Conference on Artificial Intelligence.Springer Berlin Heidelberg,2012. [10]MOHAMED A W,SABRY H Z.Constrained optimization based on modified differential evolution algorithm[J].Information Sciences,2012,194:171-208. [11]SARKER R A,ELSAYED S M,RAY T.Differential Evolution With Dynamic Parameters Selection for Optimization Problems[J].IEEE Transactions on Evolutionary Computation,2014,18(5):689-707. [12]DHADWAL M K,JUNG S N,KIM C J.Advanced particleswarm assisted genetic algorithm for constrained optimization problems[J].Computational Optimization and Applications,2014,58(3):781-806. [13]RUNARSSON T P,YAO X.Stochastic ranking for constrained evolutionary optimization[J].IEEE Transactions on Evolutionary Computation,2000,4(3):284-294. [14]ZHANG M,LUO W,WANG X.Differential evolution with dynamic stochastic selection for constrained optimization[J].Information Sciences,2008,178(15):3043-3074. [15]GUILLERMO L,COELLO C A C.A boundary search basedACO algorithm coupled with stochastic ranking[C]//IEEE Congress on Evolutionary Computation.IEEE,2007:165-172. [16]TAKAHAMA T,SAKAI S.Constrained optimization by the ε constrained differential evolution with an archive and gradient-based mutation[C]//IEEE Congress on Evolutionary Computation.IEEE,2010:1-9. [17]TAKAHAMA T,SAKAI S.Efficient constrained optimization by the ε constrained differential evolution with rough approximation using kernel regression[C]//IEEE Congress on Evolutionary Computation.IEEE,2012. [18]YANG Y,LIU J,TAN S,et al.A multi-objective differential evolutionary algorithm for constrained multi-objective optimization problems with low feasible ratio[J].Applied Soft Computing Journal,2019,80:42-56. [19]BREST J,BOSKOVIC B,ZUMER V.An improved self-adaptive differential evolution algorithm in single objective constrained real-parameter optimization[C]//Evolutionary Computation.IEEE,2010:1-8. [20]TAKAHAMA T,SAKAI S.Efficient Constrained Optimization by the ε Constrained Rank-Based Differential Evolution[C]//IEEE Congress on Evolutionary Computation.IEEE,2010. [21]HOFFMEISTER F,SPRAVE J.Problem-Independent Handling of Constraints by Use of Metric Penalty Functions[J].Evolutionary Programming,1996:289-294. [22]HOMAIFAR A,QI C X,LAI S H.Constrained Optimization Via Genetic Algorithms[J].Simulation,1994,62(4):242-253. [23]HSIEH Y,LEE Y,YOU P.Solving nonlinear constrained optimization problems:An immune evolutionary based two-phase approach[J].Applied Mathematical Modelling,2015,39(19):5759-5768. [24]KAZARLIS S,Petridis V.Varying Fitness Functions in Genetic Algorithms:Studying the Rate of Increase of the Dynamic Penalty Terms[C]//International Conference on Parallel Problem Solving from Nature.Heidelberg,Berlin:Springer,1998. [25]TESSEMA B,YEN G G.An Adaptive Penalty Formulation for Constrained Evolutionary Optimization[J].IEEE Transactions on Systems,Man,and Cybernetics-Part A:Systems and Humans,2009,39(3):565-578. [26]DE MELO V V,IACCA G.A modified Covariance Matrix Adaptation Evolution Strategy with adaptive penalty function and restart for constrained optimization[J].Expert Systems With Applications,2014,41(16):7077-7094. [27]LIN C.A rough penalty genetic algorithm for constrained optimization[J].Information Sciences,2013,241:119-137. [28]AFONSO C L,HELIO J B,HEDER S B.Variants of an adaptive penalty scheme for steady-state genetic algorithms in engineering optimization[J].Engineering Computations,2015,32(8):2182-2215. [29]POWELL D,SKOLNICK M M.Using Genetic Algorithms inEngineering Design Optimization with Non-Linear Constraints[C]//International Conference on Genetic Algorithms.Morgan Kaufmann Publishers Inc.,1993:424-431. [30]FERNANDO J,JOSÉ L V.Evolutionary Techniques for Con-strained Optimization Problems[C]//European Congress on Intelligent Techniques & Soft Computing.1999. [31]ZHOU Y,ZHU M,WANG J,et al.Tri-Goal Evolution Framework for Constrained Many-Objective Optimization[J].IEEE Transactions on Systems,Man,and Cybernetics:Systems,2020,50(8):3086-3099. [32]CAI Z,WANG Y.A Multiobjective Optimization-Based Evolutionary Algorithm for Constrained Optimization[J].IEEE Transactions on Evolutionary Computation,2006,10(6):658-675. [33]WANG Y,CAI Z,ZHOU Y,et al.An Adaptive Tradeoff Model for Constrained Evolutionary Optimization[J].IEEE Transactions on Evolutionary Computation,2008,12(1):80-92. [34]TASGETIREN M F,SUGANTHAN P N,PAN Q K,et al.An ensemble of differential evolution algorithms for constrained function optimization[J].IEEE Congress on Evolutionary Computation,2010,5(1):1-8. [35]LIN Y F,DU W,DU W L,et al.Multi-objective differential evolution with dynamic hybrid constraint handling mechanism[J].Soft Computing,2019,23(12):4341-4355. [36]LI K,CHEN R,FU G,et al.Two-Archive Evolutionary Algorithm for Constrained Multiobjective Optimization[J].IEEE Transactions on Evolutionary Computation,2019,23(2):303-315. [37]DEB K,DATTA R,INSTITUTIONEN F T O S,et al.A bi-objective constrained optimization algorithm using a hybrid evolutionary and penalty function approach[J].Engineering Optimization,2013,45(5):503-527. [38]DATTA R,DEB K.An adaptive normalization based constrained handling methodology with hybrid bi-objective and penalty function approach[C]//IEEE Congress on Evolutionary Computation.IEEE,2012:1-8. [39]DATTA R,DEB K,COSTA M F P,et al.An evolutionary algorithm based pattern search approach for constrained optimization[C]//2013 IEEE Congress on Evolutionary Computation Computation.IEEE,2013:1355-1362. [40]CAI X,HU Z,FAN Z.A novel memetic algorithm based on invasive weed optimization and differential evolution for constrained optimization[J].Soft Computing,2013,17(10):1893-1910. [41]WANG Y,CAI Z,GUO G,et al.Multiobjective Optimizationand Hybrid Evolutionary Algorithm to Solve Constrained Optimization Problems[J].IEEE Transactions on Systems,Man,and Cybernetics,Part B(Cybernetics),2007,37(3):560-575. [42]LIEPINS G E,VOSE M D.Representational issues in genetic optimization[J].Journal of Experimental & Theoretical Artificial Intelligence,1990,2(2):101-115. [43]HAN B,LEE S J.A genetic algorithm approach to measurement prescription in fault diagnosis[J].Information Sciences,1999,120(1-4):223-237. [44]XIAO J,MICHALEWICZ Z,ZHANG L,et al.Adaptive evolutionary planner/navigator for mobile robots[J].IEEE Transactions on Evolutionary Computation,1997,1(1):18-28. [45]XIAO J,MICHALEWICZ Z,ZHANG L,et al.EvolutionaryPlanner/Navigator:operator performance and self-tuning[C]//IEEE International Conference on Evolutionary Computation.1996:366-371. [46]MICHALEWICZ Z,XIAO J.Evaluation of paths in evolutionary planner/navigator[C]//International Workshop on Biologically Inspired Evolutionary Systems.1995. [47]LOZANO M,HERRERA F,KRASNOGOR N,et al.Real-Coded Memetic Algorithms with Crossover Hill-Climbing[J].Evolutionary Computation,2004,12(3):273-302. [48]HO P Y,SHIMIZU K.Evolutionary constrained optimization using an addition of ranking method and a percentage-based tolerance value adjustment scheme[J].Information Sciences,2007,177(14):2985-3004. [49]MEZURA-MONTES E,COELLO C A C.A simple multimembered evolution strategy to solve constrained optimization problems[J].IEEE Transactions on Evolutionary Computation,2005,9(1):1-17. [50]AMIRJANOV A.A changing range genetic algorithm[J].International Journal for Numerical Methods in Engineering,2004,61(15):2660-2674. [51]AMIRJANOV A.The development of a changing range genetic algorithm[J].Computer Methods in Applied Mechanics and Engineering,2006,195(19):2495-2508. [52]LIU Z,WANG Y.Handling Constrained Multiobjective Optimization Problems With Constraints in Both the Decision and Objective Spaces[J].IEEE Transactions on Evolutionary Computation,2019,23(5):870-884. [53]WHILE L,HINGSTON P.Usefulness of infeasible solutions in evolutionary search:An empirical and mathematical study[C]//Congress on evolutionary computation.2013:1363-1370. [54]DEB K,PRATAP A,MEYARIVAN T.Constrained Test Problems for Multi-objective Evolutionary Optimization[C]//Evolutionary Multi-criterion Optimization,First International Conference.Zurich,Switzerland,2001:284-298. [55]ZHANG Q F,ZHOU A M,ZHAO S Z,et al.Multiobjective optimization Test Instances for the CEC 2009 Special Session and Competition[J/OL].Mechanical engineering,2018.http://www.al-roomi.org/multimedia/CEC_Database/CEC2009/MultiObjectiveEA/CEC2009_MultiObjectiveEA_TechnicalReport.pdf. [56]CHENG P.A Tunable Constrained Test Problems Generator for Multi-objective Optimization[C]//International conference on genetic and evolutionary computing.2008:96-100. [57]FAN Z,HUANG H,LI W,et al.An opposition-based repair operator for multi-objective evolutionary algorithm in constrained optimization problems[C]//International Conference on Natural Computation.IEEE,2015:330-336. [58]HE Q,WANG L.An effective co-evolutionary particle swarm optimization for constrained engineering design problems[J].Engineering Applications of Artificial Intelligence,2007,20(1):89-99. [59]SINGH H K,ISAACS A,RAY T,et al.Infeasibility Driven Evolutionary Algorithm(IDEA) for Engineering Design Optimization[C]//AI 2008:Advances in Artificial Intelligence,21st Australasian Joint Conference on Artificial Intelligence,Auckland,New Zealand.2008. [60]KHEAWHOM S.Efficient constraint handling scheme for differential evolutionary algorithm in solving chemical engineering optimization problem[J].Journal of Industrial and Engineering Chemistry,2010,16(4):620-628. [61]COELLO C A C.Use of a self-adaptive penalty approach for engineering optimization problems[J].Computers in Industry,2000,41(2):113-127. [62]LI L D,LI X,YU X,et al.A multi-objective constraint-handling method with PSO algorithm for constrained engineering optimization problems[C]//World Congress on Computational Intelligence.2008:1528-1535. [63]MOTTE D,NORDIN A,BJARNEMO R,et al.Study of the Sequential Constraint-Handling Technique for Evolutionary Optimization With Application to Structural Problems[C]//Design Automation Conference.2011:521-531. [64]FAN Q,YAN X.Differential evolution algorithm with co-evolution of control parameters and penalty factors for constrained optimization problems[J].Asia-Pacific Journal of Chemical Engineering,2012,7(2):227-235. [65]ZOU P,RAJORA M,LIANG S Y.A new algorithm based on evolutionary computation for hierarchically coupled constraint optimization:methodology and application to assembly job-shop scheduling[J].Journal of Scheduling,2018,21(5):545-563. [66]BAI R,BURKE E K,KENDALL G,et al.A Hybrid Evolutionary Approach to the Nurse Rostering Problem[J].IEEE Transactions on Evolutionary Computation,2010,14(4):580-590. [67]BAI L,WANG J,JIANG Y,et al.Improved Hybrid Differential Evolution-Estimation of Distribution Algorithm with Feasibility Rules for NLP/MINLP Engineering Optimization Problems[J].Chinese Journal of Chemical Engineering,2012,20(6):1074-1080. [68]HU R,QIAN B.A hybrid differential evolutionary algorithm for stochastic finite buffer pipeline scheduling [J].Acta automatica Sinica,2009,35(12):1580-1586. [69]CAGNINA L C,ESQUIVEL S C,COELLO C A C.Solving Engineering Optimization Problems with the Simple Constrained Particle Swarm Optimizer[J].Informatica,2008,32(3):319-326. [70]LUCENA R R,BAIOCO J S,LIMA B S L P,et al.Optimal design of submarine pipeline routes by genetic algorithm with different constraint handling techniques[J].Advances in Engineering Software,2014,76:110-124. [71]CRUZ J M,ANDRESTORO B,HERRAN A,et al.Multiobjective optimization of the transport in oil pipelines networks[C]//Emerging Technologies and Factory Automation.2003:566-573. [72]SARKER R,RAY T.An improved evolutionary algorithm forsolving multi-objective crop planning models[J].Computers and Electronics in Agriculture,2009,68(2):191-199. [73]FAN Z,LIU J,SORENSEN T,et al.Improved Differential Evolution Based on Stochastic Ranking for Robust Layout Synthesis of MEMS Components[J].IEEE Transactions on Industrial Electronics,2009,56(4):937-948. [74]DAS S,NATARAJAN B,STEVENS D,et al.Multi-objectiveand constrained optimization for DS-CDMA code design based on the clonal selection principle[J].Applied Soft Computing,2008,8(1):788-797. [75]KONSTANTINIDIS A,YANG K.Multi-objective K-connected Deployment and Power Assignment in WSNs using a problem-specific constrained evolutionary algorithm based on decomposition[J].Computer Communications,2011,34(1):83-98. [76]PALMERS P,MCCONNAGHY T,STEYAERT M,et al.Massively multi-topology sizing of analog integrated circuits[C]//European Design and Automation Association.2009:706-711. [77]LI X,YIN M.Optimal synthesis of linear antenna array with composite differential evolution algorithm[J].Scientia Iranica.Transaction D,Computer Science & Engineering,Electrical,2012,19(6):1780. [78]SAIT S M,FAHEEMUDDIN M,MINHAS M R,et al.Multiobjective VLSI cell placement using distributed genetic algorithm[C]//Genetic And Evolutionary Computation Conference.2005:1585-1586. [79]MASAZADE E,RAJAGOPALAN R,VARSHNEY P K,et al.A Multiobjective Optimization Approach to Obtain Decision Thresholds for Distributed Detection in Wireless Sensor Networks[J].IEEE Transactions on Systems,Man,and Cybernetics,Part B(Cybernetics),2010,40(2):444-457. [80]OYAMA A,SHIMOYAMA K,FUJII K.New Constraint-Handling Method for Multi-Objective and Multi-Constraint Evolutionary Optimization[J].Transactions of the Japan Society for Aeronautical & Space Sciences,2007,50(167):56-62. [81]ERBATUR F,HASANÇEBI O,TÜTÜNCÜ Ï,et al.Optimal design of planar and space structures with genetic algorithms[J].Computers and Structures,2000,75(2):209-224. [82]COELHO R F,BERSINI H,BOUILLARD P.Parametrical mechanical design with constraints and preferences:application to a purge valve[J].Computer Methods in Applied Mechanics and Engineering,2003,192(39):4355-4378. [83]THOMPSON M P,HAMANN J D,SESSIONS J.Selection and Penalty Strategies for Genetic Algorithms Designed to Solve Spatial Forest Planning Problems[J].International Journal of Forestry Research,2009:1-14. [84]HILTON A B,CULVER T B.Constraint-handling methods for optimal groundwater remediation design by genetic algorithms[C]//Systems Man And Cybernetics.1998:3937-3942. [85]LAURA J,HARRELL S R R.Evaluation of Alternative Penalty Function Implementations in a Watershed Management Design Problem[C]//Conference on Genetic & Evolutionary Computation.1999:1551-1558. [86]HILTON A B C,CULVER T B.Constraint Handling for Genetic Algorithms in Optimal Remediation Design[J].Journal of Water Resources Planning and Management,2000,126(3):128-137. [87]SHIN S,LEE I,KIM D,et al.Multiobjective evolutionary optimization of DNA sequences for reliable DNA computing[J].IEEE Transactions on Evolutionary Computation,2005,9(2):143-158. [88]HARTEMINK A J,GIFFORD D K,KHODOR J.Automated constraint-based nucleotide sequence selection for DNA computation[J].BioSystems,1999,52(1):227-235. [89]ERBAS C,CERAV-ERBAS S,PIMENTEL A D.Multiobjective optimization and evolutionary algorithms for the application mapping problem in multiprocessor system-on-chip design[J].IEEE Transactions on Evolutionary Computation,2006,10(3):358-374. [90]KODURU P,DONG Z,DAS S,et al.A Multiobjective Evolutionary-Simplex Hybrid Approach for the Optimization of Differential Equation Models of Gene Networks[J].IEEE Transactions on Evolutionary Computation,2008,12(5):572-590. [91]SARAVANAN R,RAMABALAN S,EBENEZER N G R,et al.Evolutionary multi criteria design optimization of robot grippers[J].Applied Soft Computing Journal,2009,9(1):159-172. [92]CASTILLO O,TRUJILLO L,MELIN P.Multiple Objective Genetic Algorithms for Path-planning Optimization in Autonomous Mobile Robots[J].Soft Computing,2007,11(3):269-279. [93]LI Z W,HAO X H,ZHANG G J.Evolutionary algorithm of multi-level individual screening for protein structure prediction from scratch [J].Computer Science,2019,46(S1):80-84. [94]LIU B,FAN R X,LIU H R,et al.Learning algorithm of Bayesian network structure based on hybrid Thaliacea differential evolution algorithm [J].Journal of Communications,2019,40(7):151-161. [95]LIU D S,TAN K C,HUANG S Y,et al.On solving multiobjective bin packing problems using evolutionary particle swarm optimization[J].European Journal of Operational Research,2008,190(2):357-382. [96]TAN K C,CHEONG C Y,GOH C K.Solving multiobjective vehicle routing problem with stochastic demand via evolutionary computation[J].European Journal of Operational Research,2007,177(2):813-839. [97]OMBUKI B,ROSS B J,HANSHAR F.Multi-Objective Genetic Algorithms for Vehicle Routing Problem with Time Windows[J].Applied Intelligence,2006,24(1):17-30. [98]LIU J,YANG Y,TAN S,et al.Application of ConstrainedMulti-objective Evolutionary Algorithm in a Compressed-air Station Scheduling Problem[C]//Chinese Control Conference.2019:2023-2028. [99]LAMONT G B,SLEAR J N,MELENDEZ K.UAV Swarm Mission Planning and Routing using Multi-Objective Evolutionary Algorithms[C]//IEEE Symposium on Computational Intelligence in Multicriteria Decision Making.IEEE,2007:10-20. [100]BAKER B M,AYECHEW M A.A genetic algorithm for the vehicle routing problem[J].Computers and Operations Research,2003,30(5):787-800. [101]ZHU K Q.A diversity-controlling adaptive genetic algorithm for the vehicle routing problem with time windows[C]//IEEE International Conference on Tools with Artificial Intelligence.2003:176-183. [102]BANIAMERIAN A,BASHIRI M,TAVAKKOLI-MOGHADDAM R.Modified variable neighborhood search and genetic algorithm for profitable heterogeneous vehicle routing problem with cross-docking[J].Applied Soft Computing Journal,2019,75:441-460. [103]IBARAKI T,IMAHORI S,KUBO M,et al.Effective LocalSearch Algorithms for Routing and Scheduling Problems with General Time-Window Constraints[J].Transportation Science,2005,39(2):206-232. [104]WANG Z L,XIE T,HE K,et al.0-1 knapsack scheduling problem considering time factor[J].Computer science,2018,45(4):53-59. [105]HE Y C,WANG X Z,LI W B,et al.Exact algorithm and evolutionary algorithm for solving stochastic time-varying knapsack problem [J].Journal of software,2017,28(2):185-202. [106]ZHU Z Y,YANG Y,DENG X,et al.An efficient evolutionary algorithm for solving multi vehicle carps [J].Computer engineering and application,2008(8):212-216. [107]ALI I M,ESSAM D,KASMARIK K,et al.An Efficient Differential Evolution Algorithm for Solving 0-1 Knapsack Problems[C]//Congress on Evolutionary Computation.2018:1-8. [108]MARCONDES E J,ZANETTE B N,PERRONI P F,et al.Evolutionary Algorithms with Constraint Handling for the Hydroelectric Dispatch Planning[C]//2019 8th Brazilian Conference on Intelligent Systems(BRACIS).IEEE,2019:527-532. [109]WANG J H,WENG T,ZHANG Q.A Two-Stage Multiobjective Evolutionary Algorithm for Multiobjective Multidepot Vehicle Routing Problem With Time Windows[J].IEEE Transactions on Cybernetics,2019,49(7):2467-2478. [110]DEB K,CHAUDHURI S,MIETTINEN K.Towards estimating nadir objective vector using evolutionary approaches[C]//Genetic and Evolutionary Computation Conference(GECCO 2006).Seattle,Washington,USA,2006. |
[1] | SUN Gang, WU Jiang-jiang, CHEN Hao, LI Jun, XU Shi-yuan. Hidden Preference-based Multi-objective Evolutionary Algorithm Based on Chebyshev Distance [J]. Computer Science, 2022, 49(6): 297-304. |
[2] | ZHOU Sheng-yi, ZENG Hong-wei. Program Complexity Analysis Method Combining Evolutionary Algorithm with Symbolic Execution [J]. Computer Science, 2021, 48(12): 107-116. |
[3] | ZHAO Yang, NI Zhi-wei, ZHU Xu-hui, LIU Hao, RAN Jia-min. Multi-worker and Multi-task Path Planning Based on Improved Lion Evolutionary Algorithm forSpatial Crowdsourcing Platform [J]. Computer Science, 2021, 48(11A): 30-38. |
[4] | ZHU Han-qing, MA Wu-bin, ZHOU Hao-hao, WU Ya-hui, HUANG Hong-bin. Microservices User Requests Allocation Strategy Based on Improved Multi-objective Evolutionary Algorithms [J]. Computer Science, 2021, 48(10): 343-350. |
[5] | ZHANG Qing-qi, LIU Man-dan. Multi-objective Five-elements Cycle Optimization Algorithm for Complex Network Community Discovery [J]. Computer Science, 2020, 47(8): 284-290. |
[6] | CHEN Meng-hui, CAO Qian-feng and LAN Yan-qi. Heuristic Algorithm Based on Block Mining and Recombination for Permutation Flow-shop Scheduling Problem [J]. Computer Science, 2020, 47(6A): 108-113. |
[7] | YANG Hao, CHEN HONG-mei. Mixed-sampling Method for Imbalanced Data Based on Quantum Evolutionary Algorithm [J]. Computer Science, 2020, 47(11): 88-94. |
[8] | XIE Teng-yu,ZHOU Xiao-gen,HU Jun,ZHANG Gui-jun. Contact Map-based Residue-pair Distances Restrained Protein Structure Prediction Algorithm [J]. Computer Science, 2020, 47(1): 59-65. |
[9] | GENG Huan-tong, HAN Wei-min, ZHOU Shan-sheng, DING Yang-yang. MOEA/D Algorithm Based on New Neighborhood Updating Strategy [J]. Computer Science, 2019, 46(5): 191-197. |
[10] | JIN Ting, TAN Wen-an, SUN Yong, ZHAO Yao. Social Team Formation Method Based on Fuzzy Multi-objective Evolution [J]. Computer Science, 2019, 46(2): 315-320. |
[11] | LIU Xin-ping, GU Chun-hua, LUO Fei, DING Wei-chao. Improved NSGA-II Algorithm Based on Loser Group and Hybrid Coding Strategy [J]. Computer Science, 2019, 46(10): 222-228. |
[12] | LAI Wen-xing, DENG Zhong-min. Improved NSGA2 Algorithm Based on Dominant Strength [J]. Computer Science, 2018, 45(6): 187-192. |
[13] | CHEN Jin-yin, XIONG Hui, ZHENG Hai-bin. Parameters Optimization for SVM Based on Particle Swarm Algorithm [J]. Computer Science, 2018, 45(6): 197-203. |
[14] | SUN Qi, JIN Yan, HE Kun and XU Ling-xuan. Hybrid Evolutionary Algorithm for Solving Mixed Capacitated General Routing Problem [J]. Computer Science, 2018, 45(4): 76-82. |
[15] | LI Wei-kun, QUE Bo, WANG Wan-liang and NI Li-zhou. Multi-objective Moth-flame Optimization Algorithm Based Optimal Reactive Power Dispatch for Power System [J]. Computer Science, 2017, 44(Z11): 503-509. |
|