Abstract
In this paper a meta heuristic Particle Swarm Optimization (PSO)-based approach for the solution of the resource-constrained project scheduling problem with the purpose of minimizing project time has been developed. In order to evaluate the performance of the PSO based approach for the resource-constrained project scheduling problem, computational analyses are given. As per the results the application of PSO to project scheduling is achievable.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
References
Bakshi T.,Sarkar B., MCA Based Performance Evaluation of project selection, International Journal of software engineering & Applications (IJSEA), Vol.2, No2,2011,pp-14-22.
C.L. Hwang & K.P.Yoon, Multiple Attribute Decision Making and Introduction, London, Sage publication,1995,pp2.
Deng Lin-yi, Wang Yun –long, Lin Yan, A Particle Swarm Optimization Based on Priority Rule for Resource-Constrained Multi-Project Scheduling Problem,978-1-4244-1734-6/08/$25.00@2008 IEEE,pp-1038-1041.
M. R. Garey, D. S. Johnson, Computers and intractability: A guide to the theory of NP-completeness, New York, 1979.
W. H. Ip, Y Li, K. F. Man, K.S. Tang, Multi-product planning and scheduling using genetic algorithm approach, Computer & Industrial Engineering, Vol.38, No.2, 283-296, 2000.
P. Pongcharoen, C Hicks, P M Braiden, The development of genetic algorithm for the capacity scheduling of complex product, with multiple levels of product structure, European Journal of Operational Research, Vol.152, No.l, 215-225, 2004.
F. S. C. Lam, B. C. Lin, C. Sriskandarajah, H.Yan, Scheduling to minimize project design time using a genetic algorithm, International Journal of Production Research, Vol.37, No.6, 1369-1386, 1999.
M. Zhuang, A. Yassine, Task scheduling of parallel development projects using genetic algorithms, American Society of Mechanical Engineers Design Automation Conference. Salt Lake City, 1-11, 2004.
Kennedy J, Eberhart R C, A discrete Binary Version of the Particle Swarm Algorithm,In Proc.1997 Conf. On System, Man and Cybernetics Piscataway, NJ:IEEE Service Center, 1997,4104-4109.
Y.Shi and R.C. Eberhart,” Particle Swarm Optimization: Developments, Applications And Resources”, Proceedings of the 2001 Congress on Evolutionary Computation,Vol. 1, pp. 81-86, 2001.
R. C. Eberhart and Y. Shi, “Comparing Inertia Weights and Constriction Factor in Particle Swarm Optimization “, Proceedings of the 2000 Congress on Evolutionary Computation, Vol. 1, pp. 84-88, 2000.
J. Kennedy and R. Eberhart, “Particle Swarm Optimization “, Proc. Int. Conf. Neural Networks (ICNN), Nov. 1995, Vol. 4, pp. 1942-1948.
R, Eberhart and J. Kennedy, “A New Optimizer Using Particle Swarm Theory”, Proc. 6th Int. Symp. Micro Machine and Human Science (MHS), Oct. 1995, pp.39-43.
D. Boiringer and D. Werner, “Particle Swarm Optimization versus Genetic Algorithms for Phase Array Synthesis”, IEEE Trans. Antennas Propagat. Vol. 52, No. 3, pp. 771-779, Mar. 2004.
Y. Shi and R. Eberhart, “A Modified Particle Swarm Optimization”, Proc. IEEE World Cong. Comput. Intell., May 1998, pp. 69-73.
Y. Shi and R. Eberhart, “Empirical Study of Particle Swarm Optimization”, Proc. IEEE Cong. Evol. Comput. July 1999, Vol. 3, pp. 1945-1950.
M. Clerc and J. Kennedy, “The Particle Swarm Explosion, Stability and Convergence in a multidimensional Complex Space”, IEEE Trans. Evol. Comput. Vol. 6, No. 1, pp. 58-73, Feb. 2002.
Yamille del Valle et.al. “Particle Swarm Optimization : Basic Concepts, Variants And Applications in Power Systems”, IEEE Trans. on Evolutionary Computation,Vol. 12, No. 2, April 2008.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer India
About this paper
Cite this paper
Bakshi, T., Sinharay, A., Sarkar, B., Sanyal, S.K. (2013). A New Meta-Heuristic PSO Algorithm for Resource Constraint Project Scheduling Problem. In: Bansal, J., Singh, P., Deep, K., Pant, M., Nagar, A. (eds) Proceedings of Seventh International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012). Advances in Intelligent Systems and Computing, vol 202. Springer, India. https://doi.org/10.1007/978-81-322-1041-2_33
Download citation
DOI: https://doi.org/10.1007/978-81-322-1041-2_33
Published:
Publisher Name: Springer, India
Print ISBN: 978-81-322-1040-5
Online ISBN: 978-81-322-1041-2
eBook Packages: EngineeringEngineering (R0)