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改进的蚁群算法求解置换流水车间调度问题 被引量:3

Improved ant colony algorithm for permutation flow shop scheduling problem
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摘要 针对蚂蚁算法在求解置换流水车间调度问题时易陷入局部最优以及计算时间较长的缺点,对最大最小蚂蚁系统(MMAS)进行了改进。在该算法中,采用NEH启发式算法提高初始解质量,并通过自适应的调节策略进一步提高蚁群算法的搜索能力。运用提出的混合算法求解Taillard基准测试集,并将测试结果与其他算法进行比较,验证了该调度算法的有效性。 In order to avoid the shortcomings of ant algorithm for solving permutation flow shop scheduling problem that easily fall into local best situation and long calculation time, in this paper, an improved Max-Min Ant System (MMAS)algorithm which apply Nawaz-Enscore-Ham ( NEH ) heuristic algorithm to enhance the quality of the initial solutions and further improve the search capabil-ities through regulation of adaptive strategies is proposed . Finally we use the proposed algorithm to solve Taillard benchmarks set . Compared with other approaches , the experimental results show the effectiveness of the proposed algorithm .
作者 张丽萍
出处 《微型机与应用》 2014年第12期66-68,72,共4页 Microcomputer & Its Applications
关键词 置换流水车间调度问题 自适应 NEH启发式算法 permutation flow shop scheduling problem adaptive NEH heuristic algorithm
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参考文献4

  • 1高海兵,周驰,高亮.广义粒子群优化模型[J].计算机学报,2005,28(12):1980-1987. 被引量:102
  • 2NEARCHOU A C.The effect of various operators on the genetic search for large scheduling problems[J].International Journal of Production Economy,2004,88(1):191-203.
  • 3NAWAZ M,ENSCORE E,HAM I.A heuristic algorithm for the mmachine,n job flow shop[J].The International Journal of Management Sciences,1983,11(1):91-95.
  • 4Lian Zhigang,Gu Xingsheng,Jiao Bin.A Novel particle swarm optimization algorithm for permutation flow shop scheduling to minimize makespan[J].Chaos,Solitons and Fractals,2008,35(5):851-861.

二级参考文献10

  • 1Bergh F.,Engelbrecht A.P..Training product unit networks using cooperative particle swarm optimizers.In:Proceedings of International Joint Conference on Neural Networks,Washington,2001,1:126~131
  • 2Yoshida H.,Kawata K.,Yoshikazu F..A Particle swarm optimization for reactive power and voltage control considering voltage security assessment.IEEE Transactions on Power System,2000,15(4):1232~1239
  • 3Gao L.,Gao H.B..Particle swarm optimization based algorithm for cutting parameters selection.In:Proceedings of IEEE World Congress on Intelligent Control and Automation,Hangzhou,2004,4 :2847~ 2851
  • 4Parsopoulos K.E.,Vrahatis M.N..Recent approaches to global optimization problems through particle swarm optimiza tion.Natural Computing,2002,12(1):235~306
  • 5Salman A.,Ahmad I..Particle swarm optimization for task assignment problem.Microprocessors and Microsystems,2002,26(8):363~371
  • 6Kennedy J.,Eberhart R.C..A discrete binary version of the particle swarm algorithm.In:Proceedings of IEEE Conference on Systems,Man,and Cybernetics,Orlando,1997,5:4104~4108
  • 7Kennedy J.,Eberhart R.C..Particle swarm optimization.In:Proceedings of IEEE International Conference on Neutral Net works,Australia,1995,4:1942~1948
  • 8Shi Y.H.,Eberhart R.C..A modified particle swarm optimizer.In:Proceedings of IEEE Conference on Evolutionary Computation,Anchorage,1998,69~73
  • 9Wright A..Genetic Algorithms for Real Parameter Optimization-Foundations of Genetic Algorithms.San Mateo:Morgan Kaufmann Publishers,1991
  • 10Michalewicz Z.et al..How to Solve It:Modern Heuristics.Berlin:Springer-Verlag,2000

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