| Reference: | Andreas, N. & Omirou, S. (2006). Differential evolution for sequencing and scheduling optimization. Journal of Heuristics, 12(6), 395-411.
Blum, C (2005). Ant colony optimization: Introduction and recent trends. Physics of Life Reviews, 2(4), 353-373.
Chen, C. L., Vempati, V. S. & Aljaber, N. (1995). An application of genetic algorithms for flow shop problems. European Journal of Operational Research, 80(2), 389-396.
Chen, C. L., Neppalli, V. R. & Aljaber, N. (1996). Genetic Algorithms Applied to the Continuous Flow Shop Problem. Computers & Industrial Engineering, 30(4), 919-929.
Chen, Y. M., Chen, M. C., Chang, P. C. & Chen, S. H. (2012), Extended Artificial Chromosomes Genetic Algorithm for Permutation Flowshop Scheduling problems, Computers & Industrial Engineering, 62(2), 536–545.
Dorigo, M. (1992) Optimization, Learning and Natural Algorithm. Ph.D. Thesis, DEI, Politecnico di Milano, Italy.
Dorigo, M. & Gambardella, L. M. (1997). Ant colony system: a cooperative learning approach to the travelling salesman problem. IEEE T Evolut Comput,1,53–66.
Dorigo, M. & Stützle, T. (2004). Ant colony optimization. MIT, Cambridge.
Framinan, J., Gupta, J. N. D. & Leisten, R. (2004). A review and classification of heuristics for the permutation flowshop with makespan objective. Journal of Operational Research Society, 55, 1243–1255.
Garey, M. R., Johnson, D. S. & Sethi, R. (1976). The complexity of flowshop and jobshop scheduling. Mathematics of Operations Research, 1(2), 117-129.
Glover, F. (1996), Tabu Search and Adaptive memory programming - Advances, applications and challenges. Interfaces in Computer Science and Operations Research. Barr, Helgason and Kennington, eds., Kluwer Academic Publishers, 1-75.
Grabowski, J. & Pempera, J. (2001). New block properties for the permutation flow shop problem with application in tabu search. Journal of the Operational Research Society, 52, 210-220.
Grabowski, J. & Wodecki, M. (2004). A very fast tabu search algorithm for the permutation flowshop problem with makespan criterion. Computers & Operations Research, 31(11), 1891-1909.
Graham, R. L., Lawler, E. L., Lenstra, J. K. & Rinnooy Kan, A.H.G. (1979). Optimization and approximation in deterministic sequencing and scheduling : a survey. Annals of Discrete Mathematics, 5, 287-326.
Hejazi, S. R. & Saghafian, S. (2005). Flowshop scheduling problems with makespan criterion: a review. International Journal of Production Research, 43(14), 2895–2929.
Jin, F., Song, S.J. & Wu, C. (2007). An improved version of the NEH algorithm and its application to large-scale flow-shop scheduling problems. IIE Transactions, 39, 229-234.
Kennedy, J. & Eberhart, R. (1995). Particle swarm optimization. In Proceedings of IEEE international conference on neural network, 1942–1948.
Kuo, I. H., Horng, S. J., Kao, T. W., Lin, T. L., Lee, C. L., Terano, T. & Pan, Y. (2009). An efficient flow-shop scheduling algorithm based on a hybrid particle swarm optimization model. Expert Systems with Applications, 36(3), 7027–7032.
Lian, Z., Gu, X. & Jiao, B. (2006). A similar particle swarm optimization algorithm for permutation flowshop scheduling to minimize makespan. Applied Mathematics and Computation, 175(1), 773–785.
Lian, Z., Gu, X. & Jiao, B. (2008). A novel particle swarm optimization algorithm for permutation flow-shop scheduling to minimize makespan. Chaos, Solitons and Fractals, 35, 851–861.
Liao, C. J., Tseng, C. T. & Luarn, P. (2007). A discrete version of particle swarm optimization for flowshop scheduling problems. Computers & Operations Research, 34(10), 3099-3111.
Lin, S. W & Ying, K. C. (2011). Minimizing makespan and total flowtime in permutation flowshops by a bi-objective multi-start simulated-annealing algorithm. Computers & Operations Research, doi:10.1016/j.cor.2011.08.009.
Liu, Y. F. & Liu, S. Y. (2011). A hybrid discrete artificial bee colony algorithm for permutation flowshop scheduling problem. Applied Soft Computing doi:10.1016/j.asoc.2011.10.024.
Merkle, D. & Middendorf, M. (2000). An ant algorithm with a new pheromone evaluation rule for total tardiness problems. In: Proceedings of the EvoWorkshops, 1803(LNCS), 287–296.
Nowicki, E. & Smutnicki, C. (1996). A fast tabu search algorithm for the permutation flowshop problem. European Journal of Operational Research, 91, 160-175.
Ogbu, F. & Smith, D. (1990). The application of the simulated annealing algorithm to the solution of the n/m/Cmax flowshop problem. Computers & Operations Research, 17(3), 243-253.
Onwubolu, G. & Davendra, D. (2006). Scheduling flow shops using differential evolution algorithm. European Journal of Operational Research, 171(2), 674-692.
Osman, I. & Potts, C. (1989). Simulated annealing for permutation flow shop scheduling. OMEGA, 17(6), 551-557.
Pan, Q. K., Tasgetiren, M. F. & Liang, Y. C. (2008a). A discrete particle swarm optimization algorithm for the no-wait flowshop scheduling problem. Computer & Operations Research, 35(9), 2807-2839.
Pan, Q. K., Tasgetiren, M. F. & Liang, Y. C. (2008b). A Discrete differential evolution algorithm for the permutation flowshop scheduling problem. Computers & Industrial Engineering. 55(4), 795-816.
Rajendran, C. & Ziegler, H. (2004). Ant-colony algorithms for permutation flowshop scheduling to minimize makespan/total flowtime of jobs. European Journal of Operational Research, 155(2), 426–438.
Rameshkumar, K., Suresh, R. K. & Mohanasundaram, K. M. (2005). Discrete particle swarm optimization (DPSO) algorithm for permutation flowshop scheduling to minimize makespan. In Proceedings of the ICNC (3), 572–581.
Reeves, C. R. (1993). Improving the efficiency of tabu search for machine sequencing problem. Journal of the Operational Research Society, 44(4), 375–382.
Reeves, C. R. (1995). A genetic algorithm for flowshop sequencing. Computers & Operations Research. 22(1), 5–13.
Reeves, C. R. & Yamada, T. (1998). Genetic algorithms, path relinking and the flowshop sequencing problem. Evolutionary Computation, 6(1), 45–60.
Ruiz, R. & Maroto, C. (2005). A comprehensive review and evaluation of permutation flowshop heuristics. European Journal of Operational Research 165, 479–494.
Ruiz, R., Maroto, C. & Alcaraz, J. (2006). Two new robust genetic algorithms for the flowshop scheduling problem. OMEGA, 34, 461–47.
Ruiz, R. & Stützle, T. (2007). A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem. European Journal of Operational Research, 177(3),2033-2049.
Stützle, T. (1998a). An ant approach to the flow shop problem. In: Proceedings of the 6th European Congress on Intelligent Techniques & Soft Computing, Aachen, Germany, 3, 1560-1564.
Stützle, T. (1998b). Applying iterated local search to the permutation flowshop problem. Technical Report, AIDA-98-04, FG Intellektik, TU Darmstadt.
Taillard, E. (1990). Some efficient heuristic methods for the flow shop sequencing problem. European Journal of Operational Research, 47(1), 65–74.
Taillard, E. (1993). Benchmarks for basic scheduling problems. European Journal of Operational Research, 64(2), 278-285.
Tasgetiren, M. F., Sevkli, M., Liang, Y. C. & Gencyilmaz, G. (2004). Particle swarm optimization algorithm for permutation flowshop sequencing problem. In Proceedings of ant colony optimization and swarm intelligence (ANTS2004), LNCS 3172, Springer-Verlag, 381-89.
Watson, J. P., Barbulescu, L., Whitley, L. D. & Howe, A. E. (2002). Contrasting structured and random permutation flowshop scheduling problems: Search space topology and algorithm performance. ORSA Journal of Computing, 14(2), 98-123.
Widmer, M. & Hertz, A. (1989). A new heuristic method for the flow shop sequencing problem. European Journal of Operational Research, 41(2), 186-193.
Ying, K. C. & Liao, C.J. (2004). An ant colony system for permutation flow-shop sequencing. Computers & Operations Research, 31(5), 791-801.
Zhang, C., Jiaxu, N. & Dantong, O. (2010). A hybrid alternate two phases particle swarm optimization algorithm for flow shop scheduling problem. Computers and Industrial Engineering, 58(1), 1–11.
Zhang, J., Zhang, C. & Liang, S. (2010). The circular discrete particle swarm optimization algorithm for flow shop scheduling problem. Expert Systems with Applications, 37, 5827–5834.
Zobolas, G. I., Tarantilis, C. D. & Ioannou, G. (2009). Minimizing makespan in permutation flow shop scheduling problems using a hybrid metaheuristic algorithm. Computers & Operations Research, 36(4), 1249-1267. |
