- About this Journal
- Abstracting and Indexing
- Aims and Scope
- Article Processing Charges
- Articles in Press
- Author Guidelines
- Bibliographic Information
- Citations to this Journal
- Contact Information
- Editorial Board
- Editorial Workflow
- Free eTOC Alerts
- Publication Ethics
- Reviewers Acknowledgment
- Submit a Manuscript
- Subscription Information
- Table of Contents
Applied Computational Intelligence and Soft Computing
Volume 2011 (2011), Article ID 138078, 12 pages
Hybrid PSO-SA Type Algorithms for Multimodal Function Optimization and Reducing Energy Consumption in Embedded Systems
1INRIA Nancy—Grand Est/LORIA, 615 Rue du Jardin Botanique, 54600 Villers-Lès-Nancy, France
2LMIA—MAGE, Université de Haute-Alsace, 4 Rue des Frères Lumière, 68093 Mulhouse, France
3IECN—LORIA, Nancy-Université, Université Henri Poincaré, 54506 Vandoeuvre-Lès-Nancy, France
Received 31 December 2010; Revised 22 March 2011; Accepted 11 April 2011
Academic Editor: Chuan-Kang Ting
Copyright © 2011 Lhassane Idoumghar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- M. Locatelli, “Simulated annealing algorithms for continuous global optimization,” in Handbook of Global Optimization, P. M. Pardalos and H. E. Romeijn, Eds., vol. 2, pp. 179–230, Kluwer Academic, 2001.
- M. Pant, R. Thangaraj, and A. Abraham, “Particle swarm based metaheuristics for function optimization and engineering applications,” in Proceedings of the 7th Computer Information Systems and Industrial Management Applications (CISIM '08), vol. 7, pp. 84–90, IEEE Computer Society, Washington, DC, USA, 2008.
- J. Kennedy and C. E. Russell, “Swarm intelligence,” in Morgan Kaufmann, Academic Press, 2001.
- A. M. Marco, T. Stützle, et al., “Convergence behavior of the fully informed particle swarm optimization algorithm,” in Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation (GECCO '08), pp. 71–78, 2008.
- A. P. Engelbrecht, Fundamentals of Computational Swarm Intelligence, John Wiley & Sons, 2005.
- R. Poli, J. Kennedy, and T. Blackwell, “Particle swarm optimization. An overview,” in Swarm Intelligence, vol. 1, pp. 33–57, 2007.
- P. N. Suganthan, N. Hansen, J. J. Liang, et al., “Problem definitions and evaluation criteria for the cec 2005 special session on real-parameter optimization,” Tech. Rep. 2005005, Nanyang Technological University, Singapore; IIT Kanpur, India, 2005.
- S. Nakano, A. Ishigame, and K. Yasuda, “Consideration of particle swarm optimization combined with tabu search,” IEEJ Transactions on Electronics, Information and Systems, vol. 128, pp. 1162–1167, 2008, Special Issue on ‘The Electronics, Information and Systems Conference Electronics, Information and Systems Society, I.E.E. of Japan’.
- G. Yang, D. Chen, and G. Zhou, “A new hybrid algorithm of particle swarm optimization,” in Lecture Notes in Computer Science, vol. 4115, pp. 50–60, 2006.
- M. Bahrepour, E. Mahdipour, R. Cheloi, and M. Yaghoobi, “Super-sapso: a new sa-based pso algorithm,” in Applications of Soft Computing, vol. 58, pp. 423–430, 2009.
- M. I. Aouad, R. Schott, and O. Zendra, “A tabu search heuristic for scratch-pad memory management,” in Proceedings of the International Conference on Software Engineering and Technology (ICSET '10), vol. 64, pp. 386–390, WASET, Rome, Italy, 2010.
- S. Kirkpatrick, C. D. Gelatt Jr., and M. P. Vecchi, “Optimization by simulated annealing,” Science, vol. 220, no. 4598, pp. 671–680, 1983.
- J. Kennedy and R. C. Eberhart, “Particle swarm optimization,” in Proceedings of the IEEE International Conference on Neural Networks, pp. 1942–1948, IEEE Computer Society, 1995.
- Y. Shi and R. C. Eberhart, “A modified particle swarm optimizer,” in Proceedings of the IEEE Congress on Evolutionary Computation (CEC '98), pp. 69–73, IEEE Computer Society, 1998.
- Y. Shi and R. C. Eberhart, “Empirical study of particle swarm optimization,” in Proceedings of the Congress on Evolutionary Computation (CEC '99), pp. 1945–1950, 1999.
- W. J. Xia and Z. M. Wu, “A hybrid particle swarm optimization approach for the job-shop scheduling problem,” International Journal of Advanced Manufacturing Technology, vol. 29, no. 3-4, pp. 360–366, 2006.
- D. Chaojun and Z. Qiu, “Particle swarm optimization algorithm based on the idea of simulated annealing,” International Journal of Computer Science and Network Security, vol. 6, no. 10, pp. 152–157, 2006.
- L. Fang, P. Chen, and S. Liu, “Particle swarm optimization with simulated annealing for tsp,” in Proceedings of the 6th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases (AIKED '07), pp. 206–210, World Scientific and Engineering Academy and Society (WSEAS), Stevens Point, Wis, USA, 2007.
- X. Wang and J. Li, “Hybrid particle swarm optimization with simulated annealing,” in Proceedings of the 3rd International Conference on Machine Learning and Cybernetics (ICMLC '04), vol. 4, pp. 2402–2405, 2004.
- S. Kirkpatrick, “Optimization by simulated annealing: quantitative studies,” Journal of Statistical Physics, vol. 34, no. 5-6, pp. 975–986, 1984.
- L. Morten, K. R. Thomas, and T. Krink, Hybrid Particle Swarm Optimization with Breeding and Subpopulations, Springer, Berlin, Germany, 2000.
- “ITRS, System Drivers,” 2007, http://www.itrs.net/Links/2007ITRS/2007_Chapters/2007_SystemDrivers.pdf.
- M. I. Aouad and O. Zendra, “A survey of scratch-pad memory management techniques for low-power and -energy,” in Proceedings of the 2nd ECOOP Workshop on Implementation, Compilation, Optimization of Object-Oriented Languages, Programs and Systems (ICOOOLPS '07), pp. 31–38, Berlin, Germany, 2007.
- H. B. Fradj, A. El Ouardighi, C. Belleudy, and M. Auguin, “Energy aware memory architecture configuration,” SIGARCH Computer Architecture News, vol. 33, no. 3, pp. 3–9, 2005.
- M. Gendreau, An Introduction to Tabu Search, vol. 57, Kluwer Academic, Boston, Mass, USA, 2003.
- A. Tanenbaum, Architecture de l'ordinateur, 5th edition, 2005.
- U. P. H. Kellerer and D. Pisinger, Knapsack Problems, Springer, Berlin, Germany, 2004.
- “Benchmarks,” http://www.loria.fr/~idrissma/benchs.zip.