Abstract
In this chapter, we tackle the problem of scheduling a set of related tasks on a set of identical processors taking into account the communication delays with the objective of minimizing the maximal completion time . This problem is well known as NP-Hard. As Particle swarm optimization PSO is a promising approach for solving NP-complete problems due to its simple implementation, fast convergence and its few parameters to adjust, the main contribution of this research is to use for the first time PSO to solve the multiprocessor scheduling problem with communication delays . The proposed approach HEA-LS is a hybrid algorithm involving particle swarm optimization PSO and local search algorithm LS. Experiments conducted on several benchmarks known in the literature prove the effectiveness of our approach and show that it compares very well to the state of the art methods.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
P. Chretienne, A polynomial algorithm to optimally schedule tasks on a virtual distributed system under tree-like precedence constraints. Eur. J. Oper. 43, 225–230 (1989)
J.-Y. Colin, P. Chretienne, CPM scheduling with small communication delays. Oper. Res. 39, 680–684 (1995)
A. Daddi-Moussa, Méthode exacte pour les problèmes avec délais de communication. Thèse de Doctorat de l’Université de Paris VI (1997)
T. Davidovic, T. Crainic, Benchmark-problem instances for static scheduling of task graphs with communication delays on homogeneous multiprocessor systems. Comput. Oper. Res. 33, 2155–2177 (2006)
T. Davidovic, P. Hansen, N. Mladenovic, Variable neighborhood search for the multiprocessor scheduling problem with communication delays, in MIC 2001, Porto (2001)
D.-C. Dang, R.N. Guibadj, A. Moukrim, An effective PSO inspired algorithm for the team orienteering problem. Eur. J. Oper. Res. 229, 332–344 (2013)
J.J. Hwang, Y.C. Chow, F.D. Angers, C.Y. Lee, Scheduling graphs in systems with interprocessor communication times. J. Comput. 18, 244–257 (1989)
J. Kennedy, R. Eberhart, Particle swarm optimization, in Proceeding of IEEE International Conference on Neural Networks (1995), pp. 1942–1948
U. Kwok, I. Ahmad, Efficient scheduling of arbitrary task graphs to multiprocessors using a parallel genetic algorithm. J. Parallel Distrib. Comput. 47, 58–77 (1997)
U. Kwok, I. Ahmad, Benchmarking and comparison of the task graph scheduling algorithms. J. Parallel Distrib. Comput. 59, 381–422 (1999)
F. Omara, M. Arafa, Genetic algorithms for task scheduling problem. J. Parallel Distrib. Comput. 70, 13–22 (2010)
V.J.R. Smith, UET scheduling with Unit interprocessor communication delays. Discret. Appl. Math. 18, 55–71 (1987)
D. Tayachi, P. Chretienne, K. Mellouli, Une méthode tabou pour l’ordonnancement multiprocesseur avec délais de communication. RAIRO Oper. Res. 34, 467–485 (2000)
B. Veltman, B.J. Lageweg, J.K. Lenstra, Multiprocessor scheduling with communication delays. Parallel Comput. 16, 173–182 (1990)
M. Wu, D. Gajski, Hypertool: a programming aid for message passing systems. IEEE Trans. Parallel Distrib. Syst. 1(3), 330–343 (1990)
Acknowledgements
I would like to thank Mr. Aziz Moukrim professor at Université de Technologie de Compiegne UTC in France for his helpful remarks and suggestions to improve this work.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this chapter
Cite this chapter
Tayachi, D. (2018). Solving the P/Prec, p j ,C ij /C max Using an Evolutionary Algorithm. In: Amodeo, L., Talbi, EG., Yalaoui, F. (eds) Recent Developments in Metaheuristics. Operations Research/Computer Science Interfaces Series, vol 62. Springer, Cham. https://doi.org/10.1007/978-3-319-58253-5_22
Download citation
DOI: https://doi.org/10.1007/978-3-319-58253-5_22
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-58252-8
Online ISBN: 978-3-319-58253-5
eBook Packages: Business and ManagementBusiness and Management (R0)