Abstract
JABAT is a middleware supporting the construction of the dedicated A-Team architecture that can be used for solving variety of computationally hard optimization problems. The paper includes a general overview of the JABAT followed by a description and evaluation of the architecture designed by the authors with a view to solving RCPSP and MRCPSP instances. To construct the proposed system a number of agents, each representing a different optimization algorithm including local search, tabu search, as well as several specialized heuristics have been used. The system has been evaluated experimentally through solving a set of benchmark instances of the RCPSP and MRCPSP.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Aydin, M.E., Fogarty, T.C.: Teams of autonomous agents for job-shop scheduling problems: An Experimental Study. Journal of Intelligent Manufacturing 15(4), 455–462 (2004)
Bellifemine, F., Caire, G., Poggi, A., Rimassa, G.: JADE. A White Paper. Exp. 3(3), 6–20 (2003)
Blazewicz, J., Lenstra, J., Rinnooy, A.: Scheduling subject to resource constraints: Classification and complexity. Discrete Applied Mathematics 5, 11–24 (1983)
Lee, C.-S., Pan, C.-Y.: An intelligent fuzzy agent for meeting scheduling decision support system. Fuzzy Sets and Systems 142, 467–488 (2004)
Dorigo, M., Di Caro, G.: The Ant Colony Optimization Meta-Heuristic. In: Corne, D., Dorigo, M., Glover, F. (eds.) New Ideas in Optimization, pp. 11–32. McGraw-Hill, New York (1999)
Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading (1989)
Golden, B.L., Laptore, G., Taillard, E.D.: An adaptive memory heuristic for class of vehicle routing problems with minmax objective. Computers and Operations Research 24, 445–452 (1997)
Glover, F.: Tabu Search. Part I and II. ORSA Journal of Computing 1(3) and 2(1) (1990)
Hartmann, S., Kolisch, R.: Experimental evaluation of state-of-the-art heuristics for the resource-constrained project scheduling problem. European Journal of Operational Research 127, 394–407 (2000)
Hartmann, S., Kolisch, R.: Experimental Investigation of Heuristics for Resource-Constrained Project Scheduling: An Update. European Journal of Operational Research 174, 23–37 (2006)
Jedrzejowicz, P., Ratajczak, E.: Population Learning Algorithm for Resource-Constrained Project Scheduling. In: Pearson, D.W., Steele, N.C., Albrecht, R.F. (eds.) Artificial Neural Nets and Genetic Algorithms. Springer Computer Science, pp. 223–228. Springer, Wien (2003)
Jędrzejowicz, P., Wierzbowska, I.: JADE-Based A-Team Environment. In: Alexandrov, V.N., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds.) ICCS 2006. LNCS, vol. 3993, pp. 719–726. Springer, Heidelberg (2006)
Kennedy, J., Eberhart, R.C.: Particle swarm optimisation. In: Proc. of IEEE International Conference on Neural Networks, pp. 1942–1948 (1995)
Laborie, P.: Complete MCS-Based Search: Application to Resource Constrained Project Scheduling. In: Proceedings IJCAI-05, Edinburg, Scotland, pp. 181–186 (2005)
Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs, 2nd extended edn. Springer, Heidelberg (1994)
Oster, G.F., Wilson, E.O.: Caste and Ecology in the Social Insect. Princeton University Press, Princeton (1978)
Parunak, H.V.D.: Agents in Overalls: Experiences and Issues in the Deveopment and Deployment of Industrial Agent-Based Systems. International Journal of Cooperative Information Systems 9(3), 209–228 (2000)
PSPLIB, http://129.187.106.231/psplib
Rabak, C.S., Sichman, J.S.: Using A-Teams to optimize automatic insertion of electronic components. Advanced Engineering Informatics 17, 95–106 (2003)
Rachlin, J., Goodwin, R., Murthy, S., Akkiraju, R., Wu, F., Kumaran, S., Das, R.: A-Teams: An Agent Architecture for Optimization and Decision-Support. In: Rao, A.S., Singh, M.P., Müller, J.P. (eds.) ATAL 1998. LNCS (LNAI), vol. 1555, pp. 261–276. Springer, Heidelberg (1999)
Reynolds, R.G.: An Introduction to Cultural Algorithms. In: Sebald, A.V., Fogel, L.J. (eds.) Proc. 3rd Annual Conference on Evolutionary Programming, pp. 131–139. World Scientific, River Edge (1994)
Sprecher, A., Drexl, A.: Solving multi-mode resource-constrained project scheduling problems by a simple, general and powerful sequencing algorithm. European Journal of Operational Research 107, 431–450 (1998)
Talukdar, S., Baerentzen, L., Govek, A., Souza, P.: Asynchronous Teams: Cooperation Schemes for Autonomous, Computer-Based Agents. Technical Report EDRC 18-59-96, Carnegie Mellon University, Pittsburgh (1996)
Valls, V., Ballestin, F., Quintanilla, S.: A Population-Based Approach to the Resource-Constrained Project Scheduling Problem. Annals of Operations Research 131, 305–324 (2004)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Jedrzejowicz, P., Ratajczak-Ropel, E. (2007). Agent-Based Approach to Solving the Resource Constrained Project Scheduling Problem. In: Beliczynski, B., Dzielinski, A., Iwanowski, M., Ribeiro, B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2007. Lecture Notes in Computer Science, vol 4431. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71618-1_53
Download citation
DOI: https://doi.org/10.1007/978-3-540-71618-1_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71589-4
Online ISBN: 978-3-540-71618-1
eBook Packages: Computer ScienceComputer Science (R0)