A multi-agent system for the decentralized resource-constrained multi-project scheduling problem

International Transactions in Operational Research

Volumn 14, Issue 6, 2007, Pages 565-589

  Homberger, Jörg ^a  

^a STUTTGART UNIVERSITY OF APPLIED SCIENCES   (Germany)

Author keywords

Decentralized project scheduling; Evolution strategy; Multi agent system; Restart model

Indexed keywords

EID: 77953872113     PISSN: 09696016     EISSN: 14753995     Source Type: Journal    
DOI: 10.1111/j.1475-3995.2007.00614.x     Document Type: Article

References (94)

1. Affenzeller, M., 2002a. New variants of genetic algorithms applied to problems of combinatorial optimization. Proceedings of the EMCSR 2002, Vol. 1, Vienna, Austria, pp. 75–80.
2. Affenzeller, M., 2002b. A generic evolutionary computation approach based upon genetic algorithms and evolution strategies. Journal of Systems Science 28, 59–72.
3. Affenzeller, M., Mayrhofer, R., 2002. Generic heuristics for combinatorial optimization problems. Proceedings of the 9th International Conference on Operational Research, Minneapolis, pp. 83–92.
4. Alcaraz, J., Maroto, C., 2001. A robust genetic algorithm for resource allocation in project scheduling. Annals of Operations Research 102, 83–109.
5. Alcaraz, J., Maroto, C., Ruiz, R., 2004. Improving the performance of genetic algorithms for the resource constrained project scheduling problem. Proceedings of the 9th International Workshop on Project Management and Scheduling, Nancy, pp. 40–43.
6. Anavi-Isakow, S., Golany, B., 2003. Managing multi-project environments through constant work-in-process. International Journal of Project Management 21, 9–18.
7. Baar, T., Brucker, P., Knust, S., 1998. Tabu-search algorithms and lower bounds for the resource constrained project scheduling problem. In: Voss, S., Martello, S., Osman, I., Roucairol, C. (Eds.), Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimization. Kluwer, Dordrecht, pp. 1–8.
8. Baker, A.D., 1996. Metaphor or reality: a case study where agents bid with actual costs to schedule a factory. In: Clearwater, S.H. (Ed.), Marked-Based Control – A Paradigm for Distributed Resource Allocation. World Scientific, Singapore, pp. 184–223.
9. Beyer, H.-G., 2001. The Theory of Evolution Strategies. Springer, Heidelberg.
10. Beyer, H.-G., Schwefel, H.-P., 2002. Evolution strategies. Natural Computing 1, 3–52.
11. Blazewicz, J., Lenstra, J.K., Rinnooy Kan, A.H.G., 1983. Scheduling subject to resource constraints: classification and complexity. Discrete Applied Mathematics 5, 11–24.
12. Boctor, F.F., 1996. An adaptation of the simulated annealing algorithm for solving resource-constrained project scheduling problems. International Journal of Production Research 34, 2335–2351.
13. Boese, K.D., Kahng, A.B., Muddu, S., 1994. A new adaptive multi-start technique for combinatorial global optimizations. Operations Research Letters 16, 101–113.
14. Bonachea, D., Ingerman, E., Levy, J., McPeak, S., 2000. An improved adaptive multi-start approach to finding near-optimal solutions to the Euclidean TSP. Proceedings of the Genetic and Evolutionary Computation Conference 2000, Las Vegas, pp. 143–150.
15. Bouleimen, K., Lecocq, H., 2003. A new efficient simulated annealing algorithm for the resource constrained project scheduling problem and its multiple mode version. European Journal of Operational Research 149, 268–281.
16. Brucker, P., Drexl, A., Moehring, R., Neumann, K., Pesch, E., 1999. Resource-constrained project scheduling: notation, classification, models and methods. European Journal of Operational Research 112, 3–41.
17. Cantú-Paz, E., Goldberg, D.E., 2003. Are multiple runs of genetic algorithms better than one? Proceedings of the Genetic and Evolutionary Computation Conference 2003, Chicago, pp. 801–812.
18. Chevaleyre, Y., Dunne, P.E., Endriss, U., Lang, J., Lemaître, M., Maudet, N., Padget, J., Phelps, S., Rodríguez-Aguilar, J.A., Sousa, P., 2006. Issues in multiagent resource allocation. Informatica 30, 3–31.
19. Cho, J.H., Kim, Y.D., 1997. A simulated annealing algorithm for resource constrained project scheduling problems. Journal of the Operational Research Society 48, 736–744.
20. Coelho, J., Tavares, L., 2003. Comparative analysis of meta-heuristics for the resource constrained project scheduling problem. Technical Report, Department of Civil Engineering, Instituto Superior Tecnico, Portugal.
21. Cohen, I., Golany, B., Shtub, A., 2005. Managing stochastic, finite capacity, multi-project systems through the cross-entropy methodology. Annals of Operations Research 134, 183–199.
22. Confessore, G., Giordani, S., Rismondo, S., 2002. An auction based approach in decentralized project scheduling. Proceedings of PMS 2002 – International Workshop on Project Management and Scheduling, Valencia, pp. 110–113.
23. Confessore, G., Giordani, S., Rismondo, S., 2007. A market-based multi-agent system model for decentralized multi-project scheduling. Annals of Operations Research 150, 115–135.
24. Debels, D., Vanhoucke, M., 2005. A bi-population based genetic algorithm for the resource-constrained project scheduling problem. Lecture Notes in Computer Sciences 2483, 378–387.
25. Debels, D., Vanhoucke, M., 2006. Meta-heuristic resource-constrained project scheduling: solution space restrictions and neighbourhood extensions. Vlerick Leuven Gent Working Paper Series 2006/18.
26. Debels, D., Vanhoucke, M., 2007a. A decomposition-based genetic algorithm for the resource-constrained project scheduling problem. Operations Research 55, 457–469.
27. Debels, D., Vanhoucke, M., 2007b. Personal email correspondence. March 5, 2007.
28. Debels, D., Vanhoucke, M., 2007c. Download of the RG300 instances, http://www.projectmanagement.ugent.be/RG300Instances.php, accessed March 5, 2007.
29. Debels, D., De Reyck, B., Leus, R., Vanhoucke, M., 2006. A hybrid scatter/electromagnetism meta-heuristic for project scheduling. European Journal of Operational Research 169, 2, 638–653.
30. Drexl, A., 1991. Scheduling of project networks by job assignment. Management Science 37, 1590–1602.
31. Eiben, A.E., Schoenauer, M., 2002. Evolutionary computing. Information Processing Letters 82, 1–6.
32. Eiben, A.E., Smith, J.E., 2003. Introduction to Evolutionary Computing. Springer, Berlin.
33. Fatemi Ghomi, S.M.T., Ashjari, B., 2002. A simulation model for multi-project resource allocation. International Journal of Project Management 29, 1369–1386.
34. Fendley, L.G., 1968. Towards the development of a complete multiproject scheduling system. Journal of Industrial Engineering 19, 505–515.
35. Fink, A., 2004. Supply chain coordination by means of automated negotiations. Proceedings of the 37th Hawaii International Conference on System Sciences, Hawaii, USA.
36. Galvagnon, V., Thierry, C., 2000. Scheduling and restoring the consistency of a project in a multi-project context. Proceedings of the 2nd IFAC Conference on Management and Control of Production and Logistic, Grenoble, pp. 627–632.
37. Goldberg, D.E., 1989. Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, Reading, MA.
38. Goldberg, D.E., 2002. The Design of Innovation: Lessons from and for Competent Genetic Algorithms. Kluwer, Boston, MA.
39. Goncalves, J.F., Mendes, J.J.M., Resende, M.G.C., 2004. A genetic algorithm for the resource constrained multi-project scheduling problem. AT&T Labs Technical Report TD-668LM4, Portugal.
40. Hans, E.W., Leus, R., Wullink, G., Herroelen, W., 2007. A hierarchical approach to multi-project planning under uncertainty. OMEGA, International Journal of Management Science 35, 563–577.
41. Hartmann, S., 1998. A competitive genetic algorithm for the resource-constrained project scheduling. Naval Research Logistics 45, 733–750.
42. Hartmann, S., 2002. A self-adaptive genetic algorithm for project scheduling under resource constraints. Naval Research Logistics 49, 433–448.
43. Herdy, M., 1990. Application of the ‘Evolutionsstrategie’ to discrete optimization problems. In: Schwefel, H.-P., Männer, R. (Eds.), Parallel Problem Solving from Nature 1. Springer, Berlin, pp. 188–192.
44. Holland, J.H., 1992. Adaptation in Natural and Artificial Systems (2nd edn), MIT Press, Cambridge, MA.
45. Homberger, J., 2007. Agentcopp downloads. http://www.agentcopp.de/EN/agentcopp/downloads/, accessed March 5, 2007.
46. Homberger, J., Gehring, H., 2005. A two-phase hybrid metaheuristic for the vehicle routing problem with time windows. European Journal of Operational Research 162, 220–238.
47. Homberger, J., Kistler, S., Vullriede, R., Horstmann, J., Lanzl, R., Göttlich, T., 2005. Eine Web-Service basierte Architektur zur collaborativen Projektplanung. Proceedings of the 3rd doIT Software-Award & doIT Software-Forschungstag, Karlsruhe, pp. 87–104.
48. Jennings, N.R., Wooldridge, M., 1995. Applying agent technology. Applied Artificial Intelligence 9, 357–369.
49. Kim, S.Y., Leachman, R.C., 1993. Multi-project scheduling with explicit lateness costs. IIE Transactions 25, 34–44.
50. Knotts, G., Dror, M., Hartman, B.C., 2000. Agent-based project scheduling. IIE Transactions 32, 387–401.
51. Kochetov, Y., Stolyar, A., 2003. Evolutionary local search with variable neighborhood for the resource constrained project scheduling problem. Proceedings of the 3rd International Workshop on Computer Science and Information Technologies, Russia, 4pp. http://www.math.nsc.ru/LBRT/k5/Kochetov/Papers/Kjchetov-Ufa-03.doc, accessed April 16, 2007.
52. Kolisch, R., 1995. Project Scheduling under Resource Constraints – Efficient Heuristics for Several Problem Classes. Physica, Heidelberg.
53. Kolisch, R., 1996. Serial and parallel resource-constrained project scheduling methods revisited: theory and computation. European Journal of Operational Research 90, 320–333.
54. Kolisch, R., 2007. Library for project scheduling problems. http://129.187.106.231/psplib/, accessed September 15, 2006.
55. Kolisch, R., Drexl, A., 1996. Adaptive search for solving hard project scheduling problems. Naval Research Logistics 43, 23–40.
56. Kolisch, R., Hartmann, S., 1999. Heuristic algorithms for solving the resource-constrained project scheduling problem: classification and computational analysis. In: Weglarz, J. (Ed.), Project Scheduling: Recent Models, Algorithms and Applications. Kluwer, Dordrecht, 147–178.
57. Kolisch, R., Hartmann, S., 2006. Experimental investigation of heuristics for resource-constrained project scheduling: an update. European Journal of Operational Research 174, 23–37.
58. Krüger, A., Hilz, C., Haas, O., 2002. E-Collaboration im unternehmensübergreifenden Projekt-management. Fachzeitschrift für Information Management and Consulting 17, 46–51.
59. Kurtulus, I.S., Davis, E.W., 1982. Multi-project scheduling: categorization of heuristic rules performance. Management Science 28, 161–172.
60. Kurtulus, I.S., Narula, S.C., 1985. Multi-project scheduling: analysis of project performance. IIE Transactions 17, 58–66.
61. Leachman, R.C., Boysen, J., 1985. An aggregate model for multi-project resource allocation. In: Dean, B.V. (Ed.), Project Management: Methods and Studies. North-Holland, Amsterdam, pp. 43–64.
62. Lee, Y.-H., 2002. Market-based dynamic resource control of distributed multiple projects. Ph.D. Thesis, Pennsylvania State University, USA.
63. Lee, Y.-H., Kumara, S.R., Chatterjee, K., 2003. Multiagent based dynamic resource scheduling for distributed multiple projects using a market mechanism. Journal of Intelligent Manufacturing 14, 471–484.
64. Leon, V.J., Ramamoorthy, B., 1995. Strength and adaptability of problem-space based neighborhoods for resource-constrained scheduling. OR Spektrum 17, 173–182.
65. Li, K.Y., Willis, R.J., 1992. An iterative scheduling technique for resource constrained project scheduling. European Journal of Operational Research 56, 370–379.
66. Lova, A., Tormos, P., 2001. Analysis of scheduling schemes and heuristic rules performance in resource-constrained multiproject scheduling. Annals of Operations Research 102, 263–286.
67. Lova, A., Maroto, C., Tormos, P., 2000. A multicriteria heuristic method to improve resource allocation in multiproject scheduling. European Journal of Operational Research 127, 408–424.
68. Merkle, D., Middendorf, M., Schmeck, H., 2002. Ant colony optimization for resource-constrained project scheduling. IEEE Transaction on Evolutionary Computation 6, 333–346.
69. Mester, D., 2002. An evolutionary strategies algorithm for large scale vehicle routing problem with capacitate and time windows restrictions. Working Paper, Institute of Evolution, University of Haifa, Israel.
70. Mester, D., Bräysy, O., 2007. Active-guided evolution strategies for large-scale capacitated vehicle routing problems. Computers and Operations Research 34, 2964–2975.
71. Neumann, K., Schwindt, C., Zimmermann, J., 2003. Project Scheduling with Time Windows and Scarce Resources (2nd edn), Springer, Berlin.
72. Nissen, V., 1994. Evolutionäre Algorithmen. Deutscher-Universitätsverlag, Wiesbaden, Germany.
73. Nonobe, K., Ibaraki, T., 2002. Formulation and tabu search algorithm for the resource constrained project scheduling problem (RCPSP). In: Ribeiro, C.C., Hansen, P. (Eds.), Essays and Surveys in Metaheuristics. Kluwer, Boston, pp. 557–588.
74. Pritsker, A.A.B., Watters, L.J., Wolfe, P.M., 1969. Multiproject scheduling with limited resources: a zero-one programming approach. Management Science 16, 93–108.
75. Raidl, G., 2002. Hybrid evolutionary algorithms. Habilitationsschrift, Fakultät für Technische Naturwissenschaften und Informatik, Technische Universität Wien.
76. Rechenberg, I., 1994. Evolutionsstrategie '94. Fromman-Holzboog, Stuttgart.
77. Rismondo, S., 2006. Personal email correspondence, September 5, 2006.
78. Sandholm, T.W., 1999. Distributed rational decision making. In: Weiss, G. (Ed.), Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence. MIT Press, Cambridge, MA, 201–258.
79. Schirmer, A., 2000. Case-based reasoning and improved adaptive search for project scheduling. Naval Research Logistics 47, 201–222.
80. Schwefel, H.-P., 1995. Evolution and Optimum Seeking. Wiley, New York.
81. Shankar, V., Nagi, R., 1996. A flexible optimization approach to multi-resource, multi-project planning and scheduling. Proceedings of the 5th Industrial Engineering Research Conference, Minneapolis, pp. 263–267.
82. Shir, O.M., Bäck, T., 2005. Niching in evolution strategies. Proceedings of the Genetic and Evolutionary Computation Conference, Washington, DC, pp. 915–916.
83. Sprecher, A., Kolisch, R., Drexl, A., 1995. Semi-active, active, and non-delay schedules for the resource-constrained project scheduling problem. European Journal of Operational Research 80, 94–102.
84. Stummer, C., Vetschera, R., 2003. Decentralized planning for multiobjective resource allocation and project selection. Central European Journal of Operations Research 11, 253–279.
85. Taillard, E.D., Gambardella, L.M., Gendreau, M., Potvin, J.-Y., 2001. Adaptive memory programming: a unified view of metaheuristics. European Journal of Operational Research 134, 1–16.
86. Tormos, P., Lova, A., 2001. A competitive heuristic solution technique for resource-constrained project scheduling. Annals of Operations Research 102, 65–81.
87. Tormos, P., Lova, A., 2003a. Integrating heuristics for resource constrained project scheduling: one step forward. Technical Report, Department of Statistics and Operations Research, University of Valencia, Spain.
88. Tormos, P., Lova, A., 2003b. An efficient multi-pass heuristic for project scheduling with constrained resources. International Journal of Production Research 41, 1071–1086.
89. Tsubakitani, S., Deckro, R.F., 1990. A heuristic for multi-project scheduling with limited resources in the housing industry. European Journal of Operational Research 49, 80–91.
90. Valls, V., Ballestin, F., Quintanilla, M.S., 2002. A hybrid genetic algorithm for the resource constrained project scheduling problem with the peak crossover operator. Proceedings of the 8th International Workshop on Project Management and Scheduling, Valencia, pp. 368–371.
91. Valls, V., Ballestin, F., Quintanilla, M.S., 2005. Justification and RCPSP: a technique that pays. European Journal of Operational Research 165, 375–386.
92. Wellman, M.P., Walsh, W.E., Wurman, P.R., MacKie-Mason, J.K., 2001. Auction protocols for decentralized scheduling. Games and Economic Behavior 35, 271–303.
93. Willmes, L., Bäck, T., 2003. Evolution strategies for engineering design optimization. Proceedings of the 2nd MIT Conference on Computational Fluid and Solid Mechanics, Vol. 2, Cambridge, MA, pp. 2394–2397.
94. Zhuang, M., Yassine, A.A., 2004. Task scheduling of parallel development projects using genetic algorithms. Proceedings of the 30th Design Automation Conference, ASME 2004 International Design Engineering Technical Conferences and Computers and Information, Salt Lake City, Utah, 11pp. http://www.iese.uiuc.edu/pdlab/Papers/DETC2004-57159.pdf, accessed April 16, 2007.