Evolutionary algorithms applied to project scheduling problems - A survey of the state-of-the-art

International Journal of Production Research

Volumn 45, Issue 2, 2007, Pages 425-450

  Lancaster, John ^a   Ozbayrak, Mustafa ^b  

^a BRUNEL UNIVERSITY   (United Kingdom)

^b BAHCESEHIR UNIVERSITY   (Turkey)

Author keywords

Design structure matrix; Evolutionary algorithms; Project scheduling

Indexed keywords

COMBINATORIAL MATHEMATICS; EVOLUTIONARY ALGORITHMS; HEURISTIC METHODS; MATRIX ALGEBRA; PROBLEM SOLVING; TRAVELING SALESMAN PROBLEM;

DESIGN STRUCTURE MATRIX; META HEURISTIC; PROJECT SCHEDULING;

SCHEDULING;

EID: 33847016105     PISSN: 00207543     EISSN: 1366588X     Source Type: Journal    
DOI: 10.1080/00207540600800326     Document Type: Article

References (57)

1. Alcaraz, J. and Maroto, C., A robust genetic algorithm for resource allocation in project scheduling. Ann. Op. Res., 2001a, 102, 83-109.
2. Alcaraz, J. and Maroto, C., A new genetic algorithm for the multi-mode resource-constrained project scheduling problem. Dpto de Estadistica e Investigacion Operativa, Universidad Politecnica de Valencia Spain, 2001b.
3. Birbil, S. and Fang, S., Electromagnetism-like mechanism for global optimisation. J. Global Optim., 2003, 25, 263-282.
4. Bouleiman, K. and Lecocq, H., Multi-objective simulated annealing for the resource constrained multi-project scheduling problem. Service de Robotic et Automatisation, Université de Liege, 2000.
5. Brucker, P., Drexl, A., Mohring, R.H., Neumann, K. and Pesch, E., Resource-constrained project scheduling: an update. Euro. J. Oper. Res., 1999, 174(1), 23-37.
6. Chiu, H. and Tsai, D., A comparison of single-project and multi-project approaches in resource-constrained multi-project scheduling problems. J. Chinese Inst. Indust. Eng., 1993, 10, 171-179.
7. Debels, D. and Vanhoucke, M., An electromagnetism meta-heuristic for the resource constrained project scheduling problem. Working Paper Series, Faculteit Ecomonie and Bedrijfskunde, Universiteit Gent, 2004a.
8. Debels, D., de Reyck, B., Leus, R. and Vanhoucke, M., A hybrid scatter search/electromegnetism meta-heuristic for project scheduling. Working Paper Series, Faculteit Ecomonie and Bedrijfskunde, Universiteit Gent, 2004b.
9. Debels, D., de Reyck, B., Leus, R. and Vanhoucke, M., A scatter-search meta-heuristic for the resource constrained project scheduling problem. Euro. J. Op. Res., 2006, 169(2), 638-653.
10. Debels, D. and Vanhoucke, M., A bi-population based genetic algorithm for the resource-constrained project scheduling problem. Working Paper Series, Faculteit Economie en Bedrijfskunde, Universiteit Gent, 2005a.
11. Debels, D. and Vvanhoucke, M., A decomposition-based heuristic for the resource constrained project scheduling problem. Working Paper Series, Faculteit Economie en Bedrijfskunde, Universiteit Gent, 2005b.
12. Dorigo, M., di Caro, G. and Gambardella, L, Ant algorithms for discrete optimisation. Artif. Life, 1999, 5, 137-172.
13. Eiben, A., Hinterding, R. and Michalewicz, Z., Parameter control in evolutionary algorithms. IEEE Trans. Evol. Compu., 1999, 3(2), 124-141.
14. Eshelman, L.J. and Schaffer, D.J. Real-coded genetic algorithms and interval schema, 1992 (Foundations of Genetic Algorithms 2: Whitely, San Mateo, CA).
15. Feo, T. and Resende, M., Greedy randomised adaptive search procedure. J. Global Optim., 1995, 6, 109-133.
16. Fox, B. and Ringer, M., 1995, The Benchmarx Problems. Available online at: http://www.neosoft.com/~benchmrx/
17. Glover, F., Genetic algorithms and scatter search. Unsuspected potentials. Statist. Comp., 1994, 4, 131-140.
18. Gldberg, D., Genetic Algorithms in Search, Optimization and Machine Learning, 1989 (Addison Wesley Longman Inc.: Boston, MA).
19. Gonçalves, J., Mendes, J. and Resende, M., A genetic algorithm for the resource constrained multi-project scheduling problem. AT&T Labs Technical Report TD-668LM4, 2004.
20. Graham, R., Lawler, E., Lenstra, J. and Rinnooy Kan, A., Optimisation and approximation in deterministic sequencing and scheduling theory: a survey. Annals of Discrete Mathematics, 1979, 5, 287-326.
21. Hartmann, S., Scheduling medical research experiments - An application of project scheduling methods. Manuskripte aus den Instituten fur Betriebswirtschaftslehre, No. 452, University of Kiel, Germany, 1997.
22. Hartmann, S., A competitive genetic algorithm for resource constrained project scheduling. Naval Res. Logist., 1998, 45, 733-750.
23. Hartmann, S., Project scheduling with multiple modes: a genetic algorithm. Ann. Op. Res., 2001, 102, 111-136.
24. Hartmann, S., A self adapting genetic algorithm for project scheduling under resource constraints. Naval Res. Logist., 2002, 49, 433-448.
25. Herbots, J., Herroelen, W. and Leus, R., Experimental investigation of the applicability of ant colony optimisation algorithms for project scheduling. Department of Applied Economics, K. U. Leuvn, 2004.
26. Herroelen, W., de Reyck, B. and Demeulemeester, E., Resource contrained project scheduling: a survey of recent developments. Comput. Oper. Res., 1998, 25, 279-302.
27. Herroelen, W., Demeulemeester, E. and de Reyck, B., A note on the paper 'Resource-constrained project scheduling: notation, classification, models and methods' by Brucker et al. Euro. J. Op. Res., 2001, 128, 679-688.
28. Hindi, K., Yang, H. and Flezar, K., An evolutionary algorithm for resource constrained project scheduling. IEEE Trans. Evol. Comp., 2002, 6, 512-518.
29. Holland, J., Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence, 1992 (Massachusetts Institute of Technology Press: Cambridge, MA).
30. Kochetov, Y. and Stolyar, A., Evolutionary local search with variable neighbourhood for the resource constrained project scheduling problem, in The Workshop on Computer Science and Information Technology (CSIT), 2003.
31. Kolisch, R. and Hartmann, S., Experimental investigation of heuristics for resource constrained project scheduling: an update. Euro. J. Oper. Res., 2006, 174(1), 23-37.
32. Kolisch, R. and Sprecher, A., PSPLIB: A project scheduling problem library, Christian Albrechts Universitat zu Kiel, Germany, 1996. Available online at: http://129.187.106.231/psplib/ (accessed November 2004).
33. Kolisch, R., Sprecher, A. and Drexl, A., Characterisation and generation of a general class of Resource-Constrained project scheduling problems, 1992, Institut fur Betriebswirtschaftslehre, Universitat du Kiel.
34. Leu, S. and Yang, C., A GA-based multicriteria optimal model for construction scheduling. J. Construct. Eng. Manage., 1999, 125, 420-427.
35. Liang, Y., Chen, A., Kao, W. and Chyu, C., An ant colony approach to resource constrained project scheduling problems. Department of Industrial Engineering and Management, Yuan-Ze University, Taiwan, 2004.
36. Mendes, J., Goncalves, J. and Resende, M., A random key based genetic algorithm for the resource constrained project scheduling problem. AT&T Labs Research Technical Report TD-6DUK2C, 2005.
37. Merkle, D., Middendorf, M. and Schmeck, H., Ant colony optimisation for resource-constrained project scheduling. IEEE Trans. Evol. Comp., 2000, 6, 333-346.
38. Mori, M. and Tseng, C., A genetic algorithm for multi-mode resource constrained project scheduling problem. Euro. J. Op. Res., 1996, 100(1), 134-141.
39. Murata, T. and Ishibuchi, H., Performance evaluation of genetic algorithms for flowshop scheduling problems, in Proceedings of the First IEEE Conference on Evolutionary Computation, 2, pp. 812-817.
40. Patterson, J.H., A comparison of exact approaches for solving the multiple constrained resource, project scheduling problem. Manage. Sci., 1984, 30, 584.
41. Rogers, J., Ordering design tasks based on coupling strength, in 5th AIAA/NASA/USAF/ISSMO Symposium on Multidisciplinary Analysis and Optimisation, AIAA Paper No. 94-4326, 1994.
42. Rogers, J., Integrating a genetic algorithm into a knowledge-based system for ordering complex design process. NASA Langley Research Centre, Hampton, Virginia, 1996.
43. Schrimer, A. and Riesenberg, S., Parameterised heuristics for project scheduling - biased random sampling methods. Christian-Albrechts Universitat, Keil, Germany, 1997.
44. Sivrikaya-Şerifoǧlu, F., 1998, A new uniform order-based crossover for concurrent consideration of sequencing and selection problems. Working Paper, Abaut Izzet Baysal University, Bolu, Turkey.
45. Sriprasert, E. and Dawood, N., Genetic algorithms for multi-constraint scheduling: an application for the construction industry, Construction Informatics Digital Library. Available online at: http://itc.scix.net/paper w78-2003-341.content (accessed August 2005).
46. Starkweather, T., McDaniels, S., Mathias, K. and Whitely, C., A comparison of genetic sequencing operators, in Proceedings of the 4th International Conference on Genetic Algorithms (Morgan Kaufmann: San Mateo, CA) 1991.
47. Stewart, D., The design structure system: a method for managing the design of complex systems. IEEE Trans. Eng. Manage., 1981, 28, 71-74.
48. Todd, D., Multiple criteria genetic algorithms in engineering design and operation. PhD thesis, University of Newcastle, 1997.
49. Ulusoy, G., Sivrikaya-Şerifoǧlu, F. and Bilge, U., A genetic algorithm approach to the simultaneous scheduling of machines and automated guided vehicles. Comp. Op. Res., 1997, 24, 335-351.
50. Ulusoy, G., Sivrikaya-Şerifoǧlu, F. and Şahin, Ş., Four payment models for the multi-mode resource constrained project scheduling problem with discounted cash flows. Ann. Op. Res., 2001, 102, 237-261.
51. Valenzuela, C. and Jones, A., Evolutionary divide and conquer: a novel genetic algorithm approach to the TSP. Evol. Comp., 1993, 1, 313-333.
52. Valls, V., Quintanilla, S. and Ballestin, F., An evolutionary approach to the resource constrained project scheduling problem, in 4th Metaheuristics International Conference, Porto, Portugal, 16-20 July 2001.
53. Valls, V., Quintanilla, S. and Ballestin, F., A hybrid genetic algorithm for the resource constrained project scheduling problem with the peak crossover operator, in 8th International Workshop on Project Management and Scheduling, 2002, pp. 368-371.
54. Valls, V. Ballestin, F. and Quintanilla, S., A new crossover operator for the resource constrained project scheduling problem, in MIC2003: The Fifth Metaheuristics International Conference, 2003.
55. Wall, M., A genetic algorithm for resource-constrained scheduling. PhD thesis, Massachusetts Institute of Technology, 1996.
56. Whitfield, R., Duffy, A., Coates, G. and Hills, W., Efficient process optimisation. Concur. Engi., 2003, 11, 83-92.
57. Zhuang, M. and Yassine, A., Task scheduling of parallel development projects using genetic algorithms, in DETC ASME 2004 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Salt Lake City, Utah, USA, 2004.