Scheduling projects with multi-skilled personnel by a hybrid MILP/CP benders decomposition algorithm

Journal of Scheduling

Volumn 12, Issue 3, 2009, Pages 281-298

  Li, Haitao ^a   Womer, Keith ^a  

^a UNIVERSITY OF MISSOURI ST LOUIS   (United States)

Author keywords

Benders decomposition; Hybrid MILP CP algorithms; Multi skilled personnel; Resource constrained project scheduling

Indexed keywords

BENDERS DECOMPOSITION; BENDERS DECOMPOSITION ALGORITHM; COMPUTATIONAL STUDIES; CONSTRAINT PROGRAMMING; HYBRID MILP/CP ALGORITHMS; MIXED-INTEGER LINEAR PROGRAMMING; MULTI-SKILLED PERSONNEL; NP-HARD; OPTIMIZATION PROBLEMS; PROJECT SCHEDULING; PROJECT SCHEDULING PROBLEM; RESOURCE CONFLICT; RESOURCE-CONSTRAINED PROJECT SCHEDULING; SKILLED PERSONNEL; STAFFING COSTS; TEMPORAL ANALYSIS;

COMPUTATIONAL COMPLEXITY; COMPUTER PROGRAMMING; CONSTRAINED OPTIMIZATION; CONSTRAINT THEORY; INTEGER PROGRAMMING; LINEARIZATION; PERSONNEL; UNMANNED AERIAL VEHICLES (UAV);

SCHEDULING ALGORITHMS;

EID: 67349093890     PISSN: 10946136     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10951-008-0079-3     Document Type: Article

References (52)

1. Aksin, O. Z., Karaesmen, F., & Ormeci, E. L. (2006). A review of workforce cross-training in call centers from an operations management perspective. In D. Nembhard (Ed.), Workforce cross training handbook. Boca Raton: CRC Press.
2. Baptiste, P., Le Pape, C., & Nuijten, W. (2001). Constraint-based scheduling: applying constraint programming to scheduling problems. New York: Springer.
3. M. Bartusch R. H. Mohring F. J. Randermacher 1988 Scheduling project networks with resource constraints and time windows Annals of Operations Research 16 201 240
4. Bellenguez, O., & Neron, E. (2004). Methods for solving the multi-skill project scheduling problem. In Proceedings of the ninth international workshop on project management and scheduling, Nancy, France.
5. J. F. Benders 1962 Partition procedures for solving mixed variables programming problems Numerische Mathematik 4 238 252
6. Benoist, T., Laburthe, F., & Rotternbourg, B. (2001). Lagrange relaxation and constraint programming collaborative schemes for traveling tournament problems. In Integration of AI and OR techniques in constraint.
7. Benoist, T., Gaudin, E., & Rotternbourg, B. (2002). Constraint programming contribution to Benders decomposition: A case study. In The eighth international conference on principles and practice of constraint programming, Ithaca, New York.
8. A. Bockmayr T. Kasper 1998 A unifying framework for integer and finite domain constraint programming INFORMS Journal on Computing 10 3 287 300
9. Brucker, P. (2001). Scheduling algorithms. Berlin: Springer.
10. P. Brucker 2002 Scheduling and constraint propagation Discrete Applied Mathematicsu 123 1-3 227 256
11. Brucker, P., & Knust, S. (1998). Solving large-sized resource-constrained project scheduling problems. In J. Weglarz (Ed.), Project scheduling: recent models, algorithms and applications. Dordrecht: Kluwer Academic.
12. P. Brucker S. Knust 2000 A linear programming and constraint propagation-based lower bound for the RCPSP European Journal of Operational Research 127 2 335 362
13. P. Brucker S. Knust 2003 Lower bounds for resource-constrained project scheduling problems European Journal of Operational Research 149 302 313
14. P. Brucker A. Drexl R. H. Mohring K. Neumann E. Pesch 1999 Resource-constrained project scheduling: Notation, classification, models and methods European Journal of Operational Research 112 1 3 41
15. R. Dechter I. Meiri J. Pearl 1991 Temporal constraint networks Artificial Intelligence 49 1-3 61 95
16. Dincbas, M., Van Hentenryck, P., Simonis, H., & Aggoun, A. (1988). The constraint logic programming language CHIP. In Proceedings of the 2nd international conference on fifth generation computer systems.
17. A. Drexl A. Kimms 2001 Optimization guided lower and upper bounds for the resource investment problem Journal of Operational Research Society 52 340 351
18. Drexl, A., Juretzka, J., Salewski, F., & Schirmer, A. (1998). New modeling concepts and their impact on resource-constrained project scheduling. In J. Weglarz (Ed.), Project scheduling: recent models, algorithms and applications. Dordrecht: Kluwer Academic.
19. Easton, K., Nemhauser, G., & Trick, M. (2004). CP based branch-and-price. In M. Milano (Ed.), Constraint and integer programming. Berlin: Springer.
20. A. Eremin M. Wallace 2001 Hybrid Benders decomposition algorithms in constraint logic programming Lecture Notes in Computer Science 2239 1 15
21. Focacci, F., Laborie, P., & Nuijten, W. (2000). Solving scheduling problems with setup times and alternative resources. In Proceedings of the fifth international conference on artificial intelligence planning and scheduling.
22. Fox, M. (2006). Planning for mixed discrete continuous domains. In J. C. Beck & B. M. Smith (Eds.), Lecture notes in computer science: Vol. 3990. CPAIOR 2006 (p. 2). Berlin: Springer.
23. Fox, M., & Long, D. (2001). Hybrid STAN: Identifying and managing combinatorial optimization sub-problems in planning. In Proceedings of the international joint conference on artificial intelligence (IJCAI).
24. M. Fox D. Long 2003 PDDL2.1: An extension to PDDL for expression temporal planning domains Journal of Artificial Intelligence Research 20 61 124
25. Frank, J., & Kurklu, E. (2005). Mixed discrete and continuous algorithms for scheduling airborne astronomy observations. In R. Batak & M. Milano (Eds.), Lecture notes in computer science: Vol. 3524. CPAIOR 2005 (pp. 183-200). Berlin: Springer.
26. Harvey, W., & Ginsberg, M. (1995). Limited discrepancy search. In The fourteenth international joint conference on artificial intelligence (IJCAI-95).
27. Hooker, J. (2000). Logic-based methods for optimization: combining optimization and constraint satisfaction. New York: Wiley-Interscience.
28. J. Hooker 2002 Logic, optimization and constraint programming INFORMS Journal on Computing 14 4 285 321
29. J. Hooker M. Osorio 1999 Mixed logical-linear programming Discrete Applied Mathematics 96-97 395 442
30. ILOG (2002a). ILOG Solver 5.3 User's Manual.
31. ILOG (2002b). ILOG CPLEX 8.1 User's Manual.
32. ILOG (2002c). OPL Studio 3.6.1 User's Manual: ILOG, Inc.
33. V. Jain I. Grossmann 2001 Algorithms for hybrid MILP/CP models for a class of optimization problems INFORMS Journal on Computing 13 4 258 276
34. K. Jasen 1999 An approximation scheme for bin packing with conflicts Journal of Combinatorial Optimization 3 363 377
35. D. E. Joslin D. P. Clements 1999 "Squeaky Wheel" optimization Journal of Artificial Intelligence Research 10 353 373
36. Lasdon, L. S. (1970). Optimization theory for large systems. New York: Macmillan Co.
37. Li, H., & Womer, K. (2006a). Determining crew composition for a new technology (Working Paper).
38. H. Li K. Womer 2006 Project scheduling with multi-purpose resources: a combined MILP/CP decomposition approach International Journal of Operations and Quantitative Management 12 4 305 325
39. H. Li K. Womer 2008 Modeling the supply chain configuration problem under resource constraints International Journal of Project Management 26 6 646 654
40. Milano, M., & Trick, M. (2004). Constraint and integer programming. In M. Milano (Ed.), Constraint and integer programming: toward a unified methodology. Berlin: Springer.
41. Nemhauser, G., & Wolsey, L. (1988). Integer and combinatorial optimization. New York: Wiley.
42. Neron, E., Bellenguez, O., & Heurtebise, M. (2006). Decomposition method for solving multi-skill project scheduling problem. In Proceedings of the tenth international workshop on project management and scheduling, Poznan.
43. Neumann, K., Schwindt, C., & Zimmermann, J. (2002). Project scheduling with time windows and scarce resources: temporal and resource-constrained project scheduling with regular and nonregular objective functions. New York: Springer.
44. Schwindt, C. (1996). Generation of resource-constrained project scheduling problems with minimal and maximal time lags (Technical Report WIOR-489). Institute für Wirtschaftstheorie und Operations Research, University of Karlsruhe.
45. M. Sellmann T. Fahle 2003 Constraint programming based Lagrangian relaxation for the automatic recording problem Annals of Operations Research 118 17 33
46. A. Thesen 1977 Measures of the restrictiveness of project networks Networks 7 193 208
47. Thorsteinsson, E. S. (2001). Branch-and-check: A hybrid framework integrating mixed integer programming and constraint logic programming. In Proceedings of the seventh international conference on principles and practices of constraint programming (CP-01). Berlin: Springer.
48. Tsang, E. (1993). Foundations of constraint satisfaction. San Diego: Academic Press.
49. Van Hentenryck, P. (1999). The OPL optimization programming language. Cambridge: MIT Press.
50. B. W. Wah Y. Chen 2006 Constraint partitioning in penalty formulations for solving temporal planning problems Artificial Intelligence 170 187 231
51. Wallace, M., Novello, S., & Schimpf, J. (1997). ECLiPSe: A platform for constraint logic programming. Available from: http://www.icparc.ic.ac.uk/ eclipse/reports/eclipse/eclipse.html.
52. Xing, Z., Chen, Y., & Zhang, W. (2006). An efficient hybrid strategy for temporal planning. In J. C. Beck & B. M. Smith (Eds.), Lecture notes in computer science: Vol. 3990. CPAIOR 2006 (pp. 273-287). Berlin: Springer.