How to cite this paper
Ziaee, M. (2014). Job shop scheduling with makespan objective: A heuristic approach.International Journal of Industrial Engineering Computations , 5(2), 273-280.
Refrences
Applegate, D., & Cook, W. (1991). A computational study of the job-shop scheduling problem. ORSA Journal on Computing, 3(2) 149–156.
Asadzadeh, L., & Zamanifar, K. (2010). An agent-based parallel approach for the job shop scheduling problem with genetic algorithms. Mathematical and Computer Modelling, 52, 1957–1965.
Baker, K. (1974). Introduction to sequencing and scheduling. NewYork: Wiley.
Balas, E., & Vazacopoulos, A. (1998). Guided local search with shifting bottleneck for job shop scheduling. Management Science, 44(2), 262–275.
Blazewicz, J., Domschke, W., & Pesch, E. (1996), The job shop scheduling problem: conventional and new solution techniques. European Journal of Operational Research, 93, 1–33.
Carlier, J., & Pinson, E. (1989). An algorithm for solving the job-shop problem, Management Science, 35, 164–176.
Dell & apos; Amico, M., & Trubian, M. (1993). Applying tabu-search to the job-shop scheduling problem. Annals of Operations Research, 4, 231–252.
F?glal?, N., Ozkale, C., Engin, O., & F?glal?, A. (2009). Investigation of ant system parameter interactions by using design of experiments for job-shop scheduling problems. Computers & Industrial Engineering, 56, 538–559.
Fisher, H., & Thompson, G.L. (1963). Probabilistic learning combinations of local job shop scheduling rules. J.F. Muth, G.L. Thompson (Editors), Industrial Scheduling, Prentice-Hall, Englewood Cliffs, New Jersey, pp. 225–251.
Gao, L., Zhang, G., Zhang, L., & Li, X. (2011). An efficient memetic algorithm for solving the job shop scheduling problem. Computers & Industrial Engineering, 60(4), 699–705.
Garey, M.R., Johnson, D.S., & Sethi, R. (1976). The complexity of flow shop and job-shop scheduling. Mathematics of Operations Research, 1(2), 117–129.
Ho, N.B., Tay, J.C., & Lai, E.M.-K. (2007). An effective architecture for learning and evolving flexible job-shop schedules. European Journal of Operational Research, 179, 316–333.
Huang, K.-L., & Liao, C.-J. (2008). Ant colony optimization combined with taboo search for the job shop scheduling problem. Computers & Operations Research, 35, 1030–1046.
Jain, A.S., & Meeran, S. (1998). Deterministic job-shop scheduling: Past, present and future. European Journal of Operational Research, 113(2), 390–434.
Kammer, M., Akker, M., & Hoogeveen, H. (2011). Identifying and exploiting commonalities for the job-shop scheduling problem. Computers & Operations Research, 38(11), 1556–1561.
Kolonko, M. (1999). Some new results on simulated annealing applied to the job shop scheduling problem. European Journal of Operational Research, 113, 123–136.
Lawrence, S. (1984). Supplement to Resource constrained project scheduling: An experimental investigation of heuristic scheduling techniques. Graduate School of Industrial Administration, Carnegie Mellon University, Pittsburgh, Pennsylvania.
Lenstra, J.K. (1976). Sequencing by enumerative methods. Tech. Rep. Mathematical Centre Tract 69, Mathematisch Centrum, Amsterdam.
Lin, T.-L., Horng, S.-J., Kao, T.-W., Chen, Y.-H., Run, R.-S., Chen, R.-J., Lai, J.-L., & Kuo, I-H. (2010). An efficient job-shop scheduling algorithm based on particle swarm optimization. Expert Systems with Applications, 37, 2629–2636.
Lochtefeld, D.F., & Ciarallo, F.W. (2011). Helper-objective optimization strategies for the Job-Shop Scheduling Problem. Applied Soft Computing, 11(6), 4161–4174.
Luh, G.-C., & Chueh, C.-H. (2009). A multi-modal immune algorithm for the job-shop scheduling problem. Information Sciences, 179, 1516–1532.
Mati, Y., Dauzère-Pérès, S., & Lahlou, C. (2011), A general approach for optimizing regular criteria in the job-shop scheduling problem. European Journal of Operational Research, 212(1), 33–42.
Matsuo, H., Suh, C., & Sullivan, R. (1988). A controlled search simulated annealing method for the general job-shop scheduling problem, Tech. Rep. 03-04-88, Dept. of Management, The University of Texas, Austin.
Montgomery, D.C. (2000). Design and analysis of experiments. 5th ed., NewYork: John Wiley & Sons.
Nowicki, E., & Smutnicki, C. (1996). A fast tabu search algorithm for the job shop problem. Management Science, 42(6), 797–813.
Pezzella, F., & Merelli, E. (2000). A tabu search method guided by shifting bottleneck for the job shop scheduling problem. European Journal of Operational Research, 120, 297–310.
Pinedo, M. (2002). Scheduling: theory, algorithms and systems. Englewood cliffs, NJ: Prentice-Hall.
Ponsich, A., & Coello, C.A.C. (2013). A hybrid Differential Evolution—Tabu Search algorithm for the solution of Job-Shop Scheduling Problems. Applied Soft Computing, 13, 462–474.
Rego, C., & Duarte, R. (2009). A filter-and-fan approach to the job shop scheduling problem. European Journal of Operational Research, 194, 650–662.
Sels, V., Craeymeersch, K., & Vanhoucke, M. (2011), A hybrid single and dual population search procedure for the job shop scheduling problem. European Journal of Operational Research, 215 (3) 512–523.
Vaessens, R.J.M., Aarts, E.H.L., & Lenstra, J.K. (1996), Job shop scheduling by local search. INFORMS Journal on Computing, 8(3) 302–317.
Van Laarhoven, P., Aarts E., & Lenstra J. (1992). Job shop scheduling by simulated annealing. Operations Research, 40, 113–125.
Yamada, T., & Nakano, R. (1996), A fusion of crossover and local search, in: Proceedings of the IEEE International Conference on Industrial Technology ICIT96, Shangai, China, IEEE Press 426–430.
Zhang, C.Y., Li, P.G., Rao, Y.Q., & Guan Z.L. (2008), A very fast TS/SA algorithm for the job shop scheduling problem. Computers & Operations Research, 35, 282–294.
Zhang, R., Song, S., & Wu, C. (2013). A hybrid artificial bee colony algorithm for the job shop scheduling problem. International Journal of Production Economics, 141, 167–178.
Asadzadeh, L., & Zamanifar, K. (2010). An agent-based parallel approach for the job shop scheduling problem with genetic algorithms. Mathematical and Computer Modelling, 52, 1957–1965.
Baker, K. (1974). Introduction to sequencing and scheduling. NewYork: Wiley.
Balas, E., & Vazacopoulos, A. (1998). Guided local search with shifting bottleneck for job shop scheduling. Management Science, 44(2), 262–275.
Blazewicz, J., Domschke, W., & Pesch, E. (1996), The job shop scheduling problem: conventional and new solution techniques. European Journal of Operational Research, 93, 1–33.
Carlier, J., & Pinson, E. (1989). An algorithm for solving the job-shop problem, Management Science, 35, 164–176.
Dell & apos; Amico, M., & Trubian, M. (1993). Applying tabu-search to the job-shop scheduling problem. Annals of Operations Research, 4, 231–252.
F?glal?, N., Ozkale, C., Engin, O., & F?glal?, A. (2009). Investigation of ant system parameter interactions by using design of experiments for job-shop scheduling problems. Computers & Industrial Engineering, 56, 538–559.
Fisher, H., & Thompson, G.L. (1963). Probabilistic learning combinations of local job shop scheduling rules. J.F. Muth, G.L. Thompson (Editors), Industrial Scheduling, Prentice-Hall, Englewood Cliffs, New Jersey, pp. 225–251.
Gao, L., Zhang, G., Zhang, L., & Li, X. (2011). An efficient memetic algorithm for solving the job shop scheduling problem. Computers & Industrial Engineering, 60(4), 699–705.
Garey, M.R., Johnson, D.S., & Sethi, R. (1976). The complexity of flow shop and job-shop scheduling. Mathematics of Operations Research, 1(2), 117–129.
Ho, N.B., Tay, J.C., & Lai, E.M.-K. (2007). An effective architecture for learning and evolving flexible job-shop schedules. European Journal of Operational Research, 179, 316–333.
Huang, K.-L., & Liao, C.-J. (2008). Ant colony optimization combined with taboo search for the job shop scheduling problem. Computers & Operations Research, 35, 1030–1046.
Jain, A.S., & Meeran, S. (1998). Deterministic job-shop scheduling: Past, present and future. European Journal of Operational Research, 113(2), 390–434.
Kammer, M., Akker, M., & Hoogeveen, H. (2011). Identifying and exploiting commonalities for the job-shop scheduling problem. Computers & Operations Research, 38(11), 1556–1561.
Kolonko, M. (1999). Some new results on simulated annealing applied to the job shop scheduling problem. European Journal of Operational Research, 113, 123–136.
Lawrence, S. (1984). Supplement to Resource constrained project scheduling: An experimental investigation of heuristic scheduling techniques. Graduate School of Industrial Administration, Carnegie Mellon University, Pittsburgh, Pennsylvania.
Lenstra, J.K. (1976). Sequencing by enumerative methods. Tech. Rep. Mathematical Centre Tract 69, Mathematisch Centrum, Amsterdam.
Lin, T.-L., Horng, S.-J., Kao, T.-W., Chen, Y.-H., Run, R.-S., Chen, R.-J., Lai, J.-L., & Kuo, I-H. (2010). An efficient job-shop scheduling algorithm based on particle swarm optimization. Expert Systems with Applications, 37, 2629–2636.
Lochtefeld, D.F., & Ciarallo, F.W. (2011). Helper-objective optimization strategies for the Job-Shop Scheduling Problem. Applied Soft Computing, 11(6), 4161–4174.
Luh, G.-C., & Chueh, C.-H. (2009). A multi-modal immune algorithm for the job-shop scheduling problem. Information Sciences, 179, 1516–1532.
Mati, Y., Dauzère-Pérès, S., & Lahlou, C. (2011), A general approach for optimizing regular criteria in the job-shop scheduling problem. European Journal of Operational Research, 212(1), 33–42.
Matsuo, H., Suh, C., & Sullivan, R. (1988). A controlled search simulated annealing method for the general job-shop scheduling problem, Tech. Rep. 03-04-88, Dept. of Management, The University of Texas, Austin.
Montgomery, D.C. (2000). Design and analysis of experiments. 5th ed., NewYork: John Wiley & Sons.
Nowicki, E., & Smutnicki, C. (1996). A fast tabu search algorithm for the job shop problem. Management Science, 42(6), 797–813.
Pezzella, F., & Merelli, E. (2000). A tabu search method guided by shifting bottleneck for the job shop scheduling problem. European Journal of Operational Research, 120, 297–310.
Pinedo, M. (2002). Scheduling: theory, algorithms and systems. Englewood cliffs, NJ: Prentice-Hall.
Ponsich, A., & Coello, C.A.C. (2013). A hybrid Differential Evolution—Tabu Search algorithm for the solution of Job-Shop Scheduling Problems. Applied Soft Computing, 13, 462–474.
Rego, C., & Duarte, R. (2009). A filter-and-fan approach to the job shop scheduling problem. European Journal of Operational Research, 194, 650–662.
Sels, V., Craeymeersch, K., & Vanhoucke, M. (2011), A hybrid single and dual population search procedure for the job shop scheduling problem. European Journal of Operational Research, 215 (3) 512–523.
Vaessens, R.J.M., Aarts, E.H.L., & Lenstra, J.K. (1996), Job shop scheduling by local search. INFORMS Journal on Computing, 8(3) 302–317.
Van Laarhoven, P., Aarts E., & Lenstra J. (1992). Job shop scheduling by simulated annealing. Operations Research, 40, 113–125.
Yamada, T., & Nakano, R. (1996), A fusion of crossover and local search, in: Proceedings of the IEEE International Conference on Industrial Technology ICIT96, Shangai, China, IEEE Press 426–430.
Zhang, C.Y., Li, P.G., Rao, Y.Q., & Guan Z.L. (2008), A very fast TS/SA algorithm for the job shop scheduling problem. Computers & Operations Research, 35, 282–294.
Zhang, R., Song, S., & Wu, C. (2013). A hybrid artificial bee colony algorithm for the job shop scheduling problem. International Journal of Production Economics, 141, 167–178.