Scheduling optimization under uncertainty - An alternative approach

Computers and Chemical Engineering

Volumn 27, Issue 4, 2003, Pages 469-490

  Balasubramanian, J ^a   Grossmann, I E ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

Flowshop plants; Fuzzy numbers; MILP models; New product development; Scheduling; Tabu search; Uncertainty

Indexed keywords

FUZZY SETS; INTEGER PROGRAMMING; LINEAR PROGRAMMING; PROBABILITY DISTRIBUTIONS; PRODUCT DEVELOPMENT; PRODUCTION ENGINEERING;

PRODUCTION SCHEDULING;

SCHEDULING;

COMPUTER SIMULATOR; FUZZY MATHEMATICS; PROCESSING FACILITY; PRODUCTION MANAGEMENT; PRODUCTION SYSTEM;

ACCURACY; ARTICLE; MATHEMATICAL COMPUTING; PROBABILITY; STATISTICAL ANALYSIS; STATISTICAL MODEL;

EID: 0037445865     PISSN: 00981354     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0098-1354(02)00221-1     Document Type: Article

References (48)

1. Aarts, E. H. L., & Korst, J. (1989). Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing. New York: Wiley.
2. Abramowitz, M., & Stegun, I. A. (1972). Handbook of mathematical functions with formulas, graphs, and mathematical tables (p. 886). New York: Dover Publications.
3. Arnold, K., & Gosling, J. (1998). The JAVA programming language (2nd ed). Reading, MA: Addison-Wesley.
4. Balasubramanian, J., & Grossmann, I. E. (2002). A novel branch and bound algorithm for scheduling flowshop plants with uncertain processing times. Computers and Chemical Engineering 26, 41.
5. Battiti, R., & Tecchiolli, G. (1994). The reactive tabu search. ORSA Journal on Computing 6, 126.
6. Birewar, D. B., & Grossmann, I. E. (1989). Efficient optimization algorithms for zero-wait scheduling of multiproduct batch plants. Industrial and Engineering Chemistry Research 28, 1333.
7. Campbell, H. G., Dudek, R. A., & Smith, M. L. (1970). A heuristic algorithm for the n-job m-machine sequencing problem. Management Science 16, 630.
8. Chanas, S., & Kamburowski, J. (1981). The use of fuzzy variables in PERT. Fuzzy Sets and Systems 5, 11.
9. Chen, S.-J., & Hwang, C.-L. (1992). Fuzzy multiple attribute decision making (p. 1992). Berlin: Springer.
10. Dubois, D., & Prade, H. (1987). The mean value of a fuzzy number. Fuzzy Sets and Systems 24, 279.
11. Dubois, D., & Prade, H. (1988). Possibility theory: an approach to computerized processing of uncertainty (p. 198). New York: Plenum Press.
12. Fortemps, P. (1997). Jobshop scheduling with imprecise durations: a fuzzy approach. IEEE Transactions on Fuzzy Systems 5 (4), 557.
13. Fortemps, P., & Roubens, M. (1996). Ranking and defuzzification methods based on area compensation. Fuzzy Sets and Systems 82, 319.
14. Galluzzo, M., Ducato, R., Bartolozzi, V., & Picciotto, A. (2001). Expert control of DO in the aerobic reactor of an activated sludge process. Computers and Chemical Engineering 25, 619.
15. Glover, F. (1990). Tabu search: a tutorial. Interfaces 20, 74.
16. Hagstrom, J. N. (1988). Computational complexity of PERT problems. Networks 18, 139.
17. Hapke, M., & Slowinski, R. (1996). Fuzzy priority heuristics for project scheduling. Fuzzy Sets and Systems 83, 291.
18. Honkomp, S. J., Mockus, L., & Reklaitis, G. V. (1999). A framework for schedule evaluation with processing uncertainty. Computers and Chemical Engineering 23, 595.
19. Hui, C.-W., Gupta, A., & van der Meulen, H. A. J. (2000). A novel MILP formulation for short-term scheduling of multi-stage multiproduct batch plants with sequence-dependent constraints. Computers and Chemical Engineering 24, 2705.
20. Ierapetritou, M. G., & Pistikopoulos, E. N. (1996). Batch plant design and operations under uncertainty. Industrial and Engineering Chemistry Research 35, 772.
21. Ishibuchi, H., Yamamoto, N., Murata, T., & Tanaka, H. (1994). Genetic algorithms and neighborhood search algorithms for fuzzy flowshop scheduling problems. Fuzzy Sets and Systems 67, 81.
22. Kubic, W. L., Jr, & Stein, F. P. (1988). A theory of design reliability using probability and fuzzy sets. AIChE Journal 34, 583.
23. Lootsma, F. A. (1989). Stochastic and fuzzy PERT. European Journal of Operational Research 43, 174.
24. Malcolm, D. G., Roseboom, J. H., Clark, C. E., & Fazar, W. (1959). Application of a technique for research and development program evaluation. Operations Research 12, 16.
25. Majozi, T., Zhu, X. X. (2001). A combined fuzzy set theory and MILP approach in integration of planning and scheduling of batch plants. Presented at AIChE Annual Conference, Reno, 2001.
26. McCahon, C. S., & Lee, E. S. (1992). Fuzzy job sequencing for a flow shop. European Journal of Operational Research 62, 294.
27. McDonald, C. M., & Karimi, I. (1997). Planning and scheduling of parallel semi-continuous process. 2: Short-term scheduling. Industrial and Engineering Chemistry Research 36, 2701.
28. Nowicki, E., & Smutnicki, C. (1998). The flowshop with parallel machines: a tabu search approach. European Journal of Operational Research 106, 226.
29. Ow, P. S., & Morton, T. E. (1988). Filtered beam search in scheduling. International Journal of Production Research 26, 35.
30. Özelkan, E. C., & Duckstein, L. (1999). Optimal fuzzy counterparts of scheduling rules. European Journal of Operational Research 113, 593.
31. Pekny, J. F., & Miller, D. L. (1991). Exact solution of the no-wait flowshop scheduling problem with a comparison to heuristic methods. Computers and Chemical Engineering 15, 741.
32. Petkov, S. B., & Maranas, C. D. (1997). Multiperiod planning and scheduling of multiproduct batch plants under demand uncertainty. Industrial and Engineering Chemistry Research 36, 4864.
33. Pinto, J., & Grossmann, I. E. (1995). A continuous time mixed integer linear programming model for short-term scheduling of multistage batch plants. Industrial and Engineering Chemistry Research 34, 3037.
34. Pinto, J., & Grossmann, I. E. (1996). An alternate MILP model for short-term scheduling of batch plants with pre-ordering constraints. Industrial and Engineering Chemistry Research 35, 338.
35. Postlethwaite, B., & Edgar, C. (2000). MIMO fuzzy model-based controller. Chemical Engineering Research and Design, Part A: Transactions of the Institute of Chemical Engineers 78, 557.
36. Rajagopalan, D., & Karimi, I. A. (1989). Completion times in serial mixed-storage multiproduct processes with transfer and set-up times. Computers and Chemical Engineering 13, 175.
37. Sand, G., Engell, A., Märkert, A., Schultz, R., & Schulz, C. (2000). Approximation of an ideal online scheduler for a multiproduct batch plant. Computers and Chemical Engineering 24, 361.
38. Schmidt, C. (1998). Optimal scheduling of the agricultural chemical new product development process. Ph.D. thesis, Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA.
39. Schmidt, C., & Grossmann, I. E. (1996). Optimization models for the scheduling of testing tasks in new product development. Industrial and Engineering Chemistry Research 35, 3498.
40. Schmidt, C., & Grossmann, I. E. (2000). The exact overall time distribution of a project with uncertain task durations. European Journal of Operational Research 126 (3), 614.
41. Shah, N. (1998). Single- and multisite planning and scheduling: current status and future challenges. AIChE Symposium Series 320 (94), 75.
42. Slowinski, R. & Hapke, M. (Eds.), Scheduling under Fuzziness (2000). Heidelberg: Physica Verlag.
43. Tarifa, E., & Chiotti, O. (1995). Flexibility versus costs in multiproduct batch plant design: a calculation algorithm. Chemical Engineering Research and Design Part A: Transactions of the Institute of Chemical Engineers 73, 931.
44. van Laarhoven, P. J. M., Aarts, E. H. L., & Lenstra, J. K. (1992). Jobshop scheduling by simulated annealing. Operations Research 40, 113.
45. Wang, J. R. (1999). A fuzzy set approach to activity scheduling for product development. Journal of the Operational Research Society 50, 1217.
46. Wets, R. J.-B. (1974). Stochastic programming with fixed recourse: the equivalent deterministic program. SIAM Review 16, 309.
47. Zadeh, L. (1965). Fuzzy sets. Information and Control 8, 338.
48. Zimmermann, H.-J. (1990). Fuzzy set theory and its applications. Norwell: Kluwer Academic Publishers.