參考文獻 |
- Adams, J., Balas, E., Zawack, D. (1988). The shifting bottleneck procedure for job shop scheduling. Management Science, 34, 391-401.
- Armstrong, R., Lei, L., Gu, S. (1994). A bounding scheme for deriving the minimal cycle time of a single-transporter N-stage process with time-window constraint. European Journal of Operational Research, 78, 130-140.
- Baker, K. R. (1974). Introduction to Sequencing and Scheduling. Wiley, New York.
- Balas, E., Christofides, N. (1981). A restricted Lagrangean approach to the traveling salesman problem. Mathematical Programming, 21, 19-46.
- Balas, E., Lenstra, J. K., Vazacopoulos, A. (1995). The one-machine problem with delayed precedence constraints and its use in job shop scheduling. Management Science, 41(1), 94-109.
- Brinkmann, R., Neumann, K. (1996). Heuristic procedures for resource-constrained project scheduling with minimal and maximum time lags: The resource –leveling and minimum project duration problems. Journal of Decision Systems, 5, 129-155.
- Brucker, P., Hilbig, T., Hurink, J. (1999). A branch and bound algorithm for a single-machine scheduling problem with positive and negative time-lags. Discrete Applied Mathematics, 94, 77-99.
- Brucker, P., Jurisch, B., Kramer, A. (1994a). The job-shop problem and immediate selection. Annals of Operations Research, 50, 73-114.
- Brucker, P., Jurisch, B., Sievers, B. (1994b). A branch and bound algorithm for the job-shop scheduling problem. Discrete Applied Mathematics, 49, 107-127.
- Brucker, P., Drexl, A., Mohring, R., Neumann, K., Pesch, E. (1999). Resource-constrained project scheduling: Notation, classification, models, and methods. European Journal of Operational Research, 112, 3-41.
- Carlier, J. (1982). The one-machine sequencing problem. European Journal of Operational Research, 11, 42-47.
- Carlier, J., Pinson E. (1989). An algorithm for solving the job shop problem. Management Science, 35(2), 164-176.
- Carlier, J., Pinson, E. (1990). A practical use of Jackson’s preemptive schedule for solving the job-shop problem. Annals of Operations Research, 26, 269-287.
- Carlier, J., Pinson, E. (1994). Adjustment of heads and tails for the job-shop problem. European Journal of Operational Research, 78, 146-161.
- Caumond, A., Lacomme, P., Tchernev, N. (2008). A memetic algorithm for the job-shop with time-lags. Computers & Operations Research, 35, 2331-2356.
- Dauzere-Peres, S., Lasserre, J. B. (1993). A modified shifting bottleneck procedure for job-shop scheduling. International Journal of Production Research, 31(4), 923-932.
- Della Croce, F., Tadei, R., Volta, G. (1995). A genetic algorithm for job shop problem. Computers and Operations Research, 22, 15-24.
- Franck, B., Neumann, K., Schwindt, C. (2001). Project scheduling with calendars. OR Spektrum, 23, 325-334.
- Giffler, B., Thompson, G. L. (1960). Algorithm for solving production-scheduling problems. Operation Research, 8, 487-503.
- Heilmann, R. (2003). A branch-and-bound procedure for the multi-mode resource-constrained project scheduling problem with minimum and maximum time lags. European Journal of Operational Research, 144, 348-365.
- Herroelen, W., Reyck, B. D., Demeulemeester, E. (1998). Resource-constrained project scheduling: A survey of recent developments. Computers and Operations Research, 25, 279-302.
- Hurink, J., Keuchel, J. (2001). Local search algorithm for a single-machine scheduling problem with positive and negative time-lags. Discrete Applied Mathematics, 112, 179-197.
- Jain, A. S., Meeran, S. (1999). Deterministic job-shop scheduling: past, present and future. European Journal of Operational Research, 113, 390-434.
- Lei, L., Wang, T. J. (1991). The minimum common-cycle algorithm for cycle scheduling of time windows constraints. Management Science, 37(12), 1629-1639.
- Muth, J. F., Thompson, G. L. (1963). Industrial Scheduling. Prentice Hall: Englewood Cliffs.
- Neumann, K., Schwindt, C. (1997). Activity-on-node networks with minimal and maximal time lags and their application to make-to-order production. OR Spectrum, 19, 205-217.
- Neumann, K., Schwindt, C., Zimmermann, J. (2002). Recent results on resource-constrained project scheduling with time windows: Model, solution methods, and applications. Central European Journal of Operations Research, 10, 113-148.
- Neumann, K., Schwindt, C., Zimmermann, J. (2003). Order-based neighborhoods for project scheduling with nonregular objective functions. European Journal of Operational Research, 149, 325-343.
- Neumann, K., Zhan, J. (1995). Heuristics for the minimum project-duration problem with minimal and maximal time-lags under fixed resource constraints. Journal of Intelligent Manufacturing, 6, 145-154.
- Shapiro, G. W., Nuttle, H. W. (1998). Hoist scheduling for a PCB electroplating facility. AIIE Transactions, 20(2), 157-167.
- Sakawa, M., Mori, T. (1999). An efficient genetic algorithm for job-shop scheduling problems with fuzzy processing time and fuzzy duedate. Computers & Industrial Engineering, 36, 325-341.
- Su, L. H. (2003). A hybrid two-stage flowshop with limited waiting time constraints. Computers & Industrial Engineering, 44, 409-424.
- Sheen, G. J., Liao, L. W. (2007). A branch and bound algorithm for the one-machine scheduling problem with minimum and maximum time lags. European Journal of Operational Research, 181, 102–116.
- Park, B. J., Choi, H. R., Kim, H. S. (2003). A hybrid genetic algorithm for the job shop scheduling problems. Computers & Industrial Engineering, 45, 597–613.
- Wikum, E. D., Llewllyn, D. C., Nemhauser, G. L. (1994). One-machine generalized precedence constrained scheduling problems. Operations Research Letters, 16, 87-99.
- Yang, D. L., Chern, M. S. (1995). A two-machine flowshop sequencing problem with limited waiting time constraint. Computers & Industrial Engineering, 28, 63-70.
- Yih, Y., Liang, T. P., Moskowitz, H. (1993). Robot scheduling in a circuit board production line: a hybrid OR/ANN approach. IIE Transactions, 25(2), 26-33.
- 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.
|