A fuzzy random resource-constrained scheduling model with multiple projects and its application to a working procedure in a large-scale water conservancy and hydropower construction project

Journal of Scheduling

Volumn 15, Issue 2, 2012, Pages 253-272

  Xu, Jiuping ^a   Zhang, Zhe ^a  

^a SICHUAN UNIVERSITY   (China)

Author keywords

Fuzzy random variable; Hybrid genetic algorithm; Multiple objective; Multiple project scheduling; Resource constrained

Indexed keywords

FUZZY RANDOM VARIABLE; HYBRID GENETIC ALGORITHMS; MULTIPLE OBJECTIVES; MULTIPLE PROJECT SCHEDULING; RESOURCE-CONSTRAINED;

CONSTRUCTION INDUSTRY; FUZZY LOGIC; HYDROELECTRIC POWER; MATHEMATICAL MODELS; RANDOM VARIABLES; SCHEDULING;

GENETIC ALGORITHMS;

EID: 79955031757     PISSN: 10946136     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10951-010-0173-1     Document Type: Article

References (63)

1. Ammar, E. (2008). On solutions of fuzzy random multiobjective quadratic programming with applications in portfolio problem. Information Sciences, 178, 468-484.
2. Aytug, H., Lawley, M., et al. (2005). Executing production schedules in the face of uncertainties: a review and some future directions. European Journal of Operational Research, 161, 86-110.
3. Baptiste, P., Le Pape, C., & Nuijten, W. (2004). Constraint-based scheduling: applying constraint programming to scheduling problems. New York: Springer.
4. Bidot, J., Thierry, V., Philippe, L., & Christopher, J. (2008). A theoretic and practical framework for scheduling in a stochastic environment. Journal of Scheduling, 10, 41-65.
5. Brucker, P. (2004). Scheduling algorithms. Berlin: Springer.
6. Brucker, P., Knust, S., et al. (1998). A branch and bound algorithm for the resource-constrained project scheduling problem. European Journal of Operational Research, 107, 272-288.
7. Brucker, P., Drexl, A., et al. (1999). Resource constrained project scheduling: notation, models and methods. European Journal of Operational Research, 112, 3-41.
8. Chiarandini, M., Birattari, M., et al. (2006). An effective hybrid algorithm for university course timetabling. Journal of Scheduling, 9, 403-432.
9. Choi, J., Realff, M. J., & Lee, J. H. (2004). Dynamic programming in a heuristically confined state space: a stochastic resourceconstrained project scheduling application. Computers and Chemical Engineering, 28, 1039-1058.
10. Colubi, A., Domonguez-Menchero, J., et al. (2001). On the formalization of fuzzy random variables. Information Sciences, 133, 3-6.
11. Detti, P. (2008). Algorithms for multiprocessor scheduling with two job lengths and allocation restrictions. Journal of Scheduling, 11, 205-212.
12. Drexl, A. (1991). Scheduling of project networks by job assignment. Management Science, 37, 1590-1602.
13. Dutta, P., Chakraborty, D., & Roy, A. (2005). A single-period inventory model with fuzzy random variable demand. Mathematical and Computer Modelling, 41, 915-922.
14. Franck, B., Neumann, K., & Schwindt, C. (2001). Truncated branch bound, schedule-construction, for resource-constrained project scheduling. OR Spektrum, 23, 297-324.
15. Freeman, R. J. (1960a). A generalized PERT. Operations Research, 8, 281.
16. Freeman, R. J. (1960b). A generalized network approach to project activity sequencing. IRE Transactions on Engineering Management, 7, 103-107.
17. Fricke, S. E., & Shenhar, A. J. (2000). Managing multiple engineering projects in a manufacturing support environment. IEEE Transactions on Engineering Management, 17, 258-268.
18. Garey, M. R., & Johnson, D. S. (1979). Computers and intractability. A guide to the theory of NP-completeness. New York: Freeman.
19. Gen, M., & Cheng, R. (2000). Genetic algorithm and engineering optimization. New York: Wiley.
20. Gil, M., Lopez-Diaz, M., & Ralescu, D. (2006). Overview on the development of fuzzy random variables. Fuzzy Sets and Systems, 157, 2546-2557.
21. Golenko-Ginzburg, D., & Gonik, A. (1997). Stochastic network project scheduling with non-consumable limited resources. International Journal of Production Economics, 48, 29-37.
22. Herroelen, W., & Leus, R. (2005). Project scheduling under uncertainty: survey and research potentials. European Journal of Operational Research, 165, 289-306.
23. Holland, J. H. (1975). Adaptation in natural and artificial systems. Ann Arbor: University of Michigan Press.
24. Ishii, H., & Tada, M. (1995). Single machines scheduling problem with fuzzy precedence relation. European Journal of Operational Research, 87, 284-288.
25. Johannes, B. (2006). Scheduling parallel jobs to minimize the makespan. Journal of Scheduling, 9, 433-452.
26. Julien, B., Thierry, V., Philippe, L., & Christopher, J. (2008). A theoretic and practical framework for scheduling in a stochastic environment. Journal of Scheduling, 10, 41-65.
27. Kim, K., Yun, W., et al. (2005). Hybrid genetic algorithm with adaptive abilities for resource-constrained multiple project scheduling. Computers in Industry, 56, 143-160.
28. Kwakernaak, H. (1978). Fuzzy random variables, I: definitions and theorems. Information Sciences, 1-29.
29. Kwakernaak, H. (1979). Fuzzy random variables, II: algorithms and examples for the discrete case. Information Sciences, 253-278.
30. Lee, M., & Takagi, H. (1979). Dynamic control of genetic algorithm using fuzzy logic techniques. In Proceedings of the 5th international conference on genetic algorithms (pp. 76-83). San Francisco: Morgan Kaufmann.
31. Li, J., & Xu, J. (2009). A novel portfolio selection model in a hybrid uncertain environment. The International Journal of Management Science, 37, 439-449.
32. Li, J., Xu, J., & Gen, M. (2006). A class of multiobjective linear programming model with fuzzy random coefficients. Mathematical and Computer Modelling, 44, 1097-1113.
33. Liu, Y., & Liu, B. (2003). Fuzzy random variables: a scalar expected value operator. Fuzzy Optimization and Decision Making, 143-160.
34. Lorterapong, P. (1994). A fuzzy heuristic method for resourceconstrained project scheduling. Project Management Journal, 25, 12-18.
35. Lova, A., & Tormos, P. (2002). Combining random sampling and backward-forward heuristics for resource-constrained multiproject scheduling. In Proceedings of the 8th conference on project management and scheduling (pp. 244-248).
36. Lova, A., Maroto, C., & Tormos, P. (2000). Analysis of scheduling schemes & heuristic rules performance in resource-constrained multiple project scheduling. Annals of Operations Research, 102, 408-424.
37. Luhandjula, M. (1987). Multiple objective programming problems with possibility coefficients. Fuzzy Sets and Systems, 21, 135-145.
38. Möller, B., & Beer, M. (2004). Fuzzy randomness-uncertainty in civil engineering and computational mechanics. Berlin: Springer.
39. Möller, B., & Reuter, U. (2007). Uncertainty forecasting in engineering. Berlin: Springer.
40. Neumann, K., & Schwindt, C. (2002). Project scheduling with inventory constraints. Mathematical Methods of Operations Research, 56, 513-533.
41. Pinedo, M. (2002). Scheduling: theory, algorithms, and systems. New York: Prentice Hall.
42. Potts, C., & Kovalyov, M. (2000). Scheduling with batching: a review. European Journal of Operational Research, 120, 228-249.
43. Prade, H. (1979). Using fuzzy set theory in a scheduling problem: a case study. Fuzzy Sets and Systems, 2, 153-165.
44. Puri, M., & Ralescu, D. (1986). Fuzzy random variables. Journal of Mathematical Analysis and Applications, 114, 409-422.
45. Roy, U., & Zhang, X. (1996). A heuristic approach to n/m job shop fuzzy dynamic scheduling algorithms. Production Planning and Control, 7, 299-311.
46. Scheiberg, M., & Stretton, J. (1994). Multiproject planning: Turing portfolio indices. International Journal of Project Management, 12, 107-114.
47. Song, Q., Leland, R., & Chissom, B. (1995). A new fuzzy time-series model of fuzzy number observations. Fuzzy Sets and Systems, 73, 341-348.
48. Sullivan, J., & Woodall, W. (1994). A comparison of fuzzy forecasting and Markov modeling. Fuzzy Sets and Systems, 64, 279-293.
49. Syswerda, G. (1991) Scheduling optimization using genetic algorithms. Princeton: Van Nostrand Reinhold.
50. Timpe, C., & Kallrath, J. (2000). Optimal planning in large multi-site production networks. European Journal of Operational Research, 126, 422-435.
51. Tormos, P., & Lova, A. (2001). A competitive heuristic solution technique for resource-constrained project shedding. Annals of Operations Research, 102, 65-81.
52. Vercellis, C. (1994). Constrained multi-project planning problems: a Lagrangean decomposition approach. European Journal of Operational Research, 78, 267-275.
53. Vonder, V., Demeulemeester, S., et al. (2005). The use of buffers in project management: the trade-off between stability and makespan. International Journal of Production Economics, 97, 227-240.
54. Wang, S., & Watada, J. (2009). Fuzzy random renewal reward process and its applications. Information Sciences, 179, 4057-4069.
55. Wang, P., Wang, G., & Hu, Z. (1997). Speeding up the search process of genetic algorithm by fuzzy logic. In Proceedings of the fifth European congress on intelligent techniques and soft computing (pp. 665-671).
56. Wang, S., Liu, Y., & Watada, J. (2009). Fuzzy random renewal process with queuing applications. Computers and Mathematics with Applications, 57, 1232-1248.
57. Xu, J., & Liu, Y. (2008). Multi-objective decision making model under fuzzy random environment and its application to inventory problems. Information Sciences, 178, 2899-2914.
58. Xu, H., & Vukovich, G. (1994). Fuzzy evolutionary algorithm and automatic robot trajectory generation. In Proceedings of the first IEEE conference on evolutionary computation (pp. 595-600). Piscataway: IEEE Press.
59. Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338-353.
60. Zadeh, L. A. (1978). Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1, 3-28.
61. Zeng, X., & Rabenasolo, B. (1997) A fuzzy logic based design for adaptive genetic algorithms. In Proceedings of the 5th European congress on intelligent techniques and soft computing (pp. 660-664).
62. Zhu, G., Bard, J., & Yu, G. (2007). A two-stage stochastic programming approach for project planning with uncertain activity durations. Journal of Scheduling, 10, 167-180.
63. Zimmermann, H. J. (1978). Fuzzy linear programming with several objective functions. Fuzzy Sets and System, 1, 46-55.