[1] |
Vallada E, Rubn R. Cooperative metaheuristics for the permutation flowshop scheduling problem. European Journal of Operational Research, 2009, 193(2): 365-376 |
[2] |
[2] Vallada E, Rubn R, Gerardo M. Minimising total tardiness in the m-machine flowshop problem: a review and evaluation of heuristics and metaheuristics. Computers Operations Research, 2008, 35(4): 1350-1373 |
[3] |
[3] Liao J M, Huang C J. Tabu search for non-permutation flowshop scheduling problem with minimizing total tardiness. Applied Mathematics and Computation, 2010, 217(2): 557-567 |
[4] |
[4] Hasija S, Rajendran C. Scheduling in flowshops to minimize total tardiness of jobs. International Journal of Production Research, 2004, 42(11): 2289-2301 |
[5] |
[5] Armentano V A, Ronconi D P. Tabu search for total tardiness minimization in flowshop scheduling problems. Computers Operations Research, 1999, 26(3): 219-235 |
[6] |
[6] Talip K, Bilal T, John W. Elite guided steady-state genetic algorithm for minimizing total tardiness in flowshops. Computers Industrial Engineering, 2010, 58(2): 300-306 |
[7] |
[7] Li B B, Wang L, Liu B. An effective PSO-based hybrid algorithm for multi-objective permutation flow shop scheduling. IEEE Transactions on Systems, Man, and Cybernetics --Part A: Systems and Humans, 2008, 38(4): 818-831 |
[8] |
Jiao Li-Cheng, Liu Jing, Zhong Wei-Cai, Coevolutionary Computation and Multiagent Systems. Beijng: Science Press, 2006. 205-224(焦李成, 刘静, 钟伟才. 协同进化计算与多智能体系统. 北京: 科学出版社, 2006. 205-224) |
[9] |
[9] Sarker R A, Ray T. Agent-Based Evolutionary Search. Berlin: Springer-Verlag, 2010. 97-116 |
[10] |
Zhong Wei-Cai, Liu Jing, Jiao Li-Cheng. Optimal approximation of linear systems by multi-agent genetic algorithm. Acta Automatica Sinica, 2004, 30(6): 933-938(钟伟才, 刘静, 焦李成. 多智能体遗传算法用于线性系统逼近. 自动化学报, 2004, 30(6): 933-938) |
[11] |
Sttzle T. Applying iterated local search to the permutation flow shop problem, Technical Report, AIDA-98-04, FG Intellektik, FB Informatik, TU Darmstadt, 1998 |
[12] |
Osman I, Potts C. Simulated annealing for permutation flow-shop scheduling. Omega, 1989, 17(6): 551-557 |
[13] |
Montgomery D C. Design and Analysis of Experiments (5th Edition). Hoblken: John Wiley and Sons, 2000 |
[14] |
Ruiz R, Maroto C, Alcaraz J. Two new robust genetic algorithms for the flowshop scheduling problem. Omega, 2006, 34(5): 461-476 |
[15] |
Parthasarathy S, Rajendran C. A simulated annealing heuristic for scheduling to minimize mean weighted tardiness in a flowshop with sequence-dependent setup times of jobs --a case study. Production Planning and Control, 1997, 8(5): 475-483 |
[16] |
Hasija S, Rajendran C. Scheduling in flowshops to minimize total tardiness of jobs. International Journal of Production Research, 2004, 42(11): 2289-2301 |
[17] |
Vallada E, Rubn R. Genetic algorithms with path relinking for the minimum tardiness permutation flowshop problem. Omega, 2010, 38(1-2): 57-67 |
[18] |
Ruiz R, Sttzle T. A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem. European Journal of Operational Research, 2007, 177(3): 2033-2049 |
[19] |
Zemel E. Measuring the quality of approximate solutions to zero-one programming problems. Mathematics of Operations Research, 1981, 6(3): 319-332 |
[20] |
Kim Y D. Heuristics for flowshop scheduling problems minimizing mean tardiness. Journal of the Operational Research Society, 1993, 44(1): 19-28 |
[21] |
Kim Y D, Lim H G, Park M W. Search heuristics for a flow shop scheduling problem in a printed circuit board assembly process. European Journal of Operational Research, 1996, 91(1): 124-143 |