Implementing metaheuristic optimization algorithms with JECoLi

ISDA 2009 - 9th International Conference on Intelligent Systems Design and Applications

Volumn , Issue , 2009, Pages 505-510

  Evangelista, Pedro ^a   Maia, Paulo ^a   Rocha, Miguel ^a  

^a UNIVERSITY OF MINHO   (Portugal)

Author keywords

[No Author keywords available]

Indexed keywords

APPLICATION FIELDS; EVOLUTIONARY COMPUTATIONS; METAHEURISTIC OPTIMIZATION; OPEN-SOURCE;

BIOINFORMATICS; HEURISTIC METHODS; INTELLIGENT SYSTEMS; OPTIMIZATION;

COMPUTATIONAL EFFICIENCY;

EID: 77949517125     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISDA.2009.161     Document Type: Conference Paper

References (23)

1. E. Alba and B. Dorronsoro. Cellular genetic algorithms. Springer Verlag, 2008.
2. K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE transactions on evolutionary computation, 6(2):182-197, 2002.
3. P. Evangelista, I. Rocha, E. Ferreira, and M. Rocha. Evolutionary approaches for strain optimization using dynamic models under a metabolic engineering perspective. In C. Pizzuti and M. Ritchie, editors, Proceedings of the Evo-Bio 2009, Lecture Notes Computer Science, 2009.
4. L. Fogel. Intelligence Through Simulated Evolution: Forty Years of Evolutionary Programming. John Wiley and Sons, New York, 1999.
5. J. Holland. Adaptation in Natural and Artificial Systems. PhD thesis, University of Michigan, Ann Arbor, 1975.
6. J. Kennedy and R. Eberhart. Particle swarm optimization. In Proceedings of IEEE International Conference on Neural Networks, pages 1942-1948. IEEE Press, 1995.
7. S. Kirkpatrick, C. D. G. Jr., and M. P. Vecchi. Optimization by simulated annealing. Science, 220(4598):671-680, 1983.
8. J. Koza. Genetic programming: on the programming of computers by means of natural selection. MIT press, 1992.
9. D. Machado and M. Rocha. getalife - an artificial life environment for the evaluation of agent-based systems and evolutionary algorithms for reinforcement learning. In New Challenges in Applied Intelligence Technologies, Proc. of the IEA-AIE 2008 conference, Studies in Computational Intelligence Series. Springer, 2008.
10. P. Maia, E. C. Ferreira, I. Rocha, and M. Rocha. Evaluating evolutionary multiobjective algorithms for the in silico optimization of mutant strains. In 8th IEEE International Conference on BioInformatics and BioEngineering Workshops(BIBE2008). Athens, Greece, pages 509-514, 2008.
11. R. Mendes, I. Rocha, E. Ferreira, and M. Rocha. A comparison of algorithms for the optimization of fermentation processes. In 2006 IEEE Congress on Evolutionary Computation, pages 7371-7378, Vancouver, BC, Canada, jul 2006.
12. P. Moscato and M. Norman. A 'Memetic' Approach for the Traveling Salesman Problem. Implementation of a Computational Ecology for Combinatorial Optimization on Message-Passing Systems. In M. Valero, E. Onate, M. Jane, J. L. Larriba, and B. Suarez, editors, Parallel Computing and Transputer Applications, pages 187-194, Amsterdam, 1992. IOS Press.
13. M. Rocha, P. Cortez, and J. Neves. Evolution of neural networks for classification and regression. Neurocomputing, 70(16-18), oct 2007.
14. M. Rocha, P. Maia, R. Mendes, E. C. Ferreira, K. Patil, J. Nielsen, and I. Rocha. Natural computation metaheuristics for the in silico optimization of microbial strains. BMC Bioinformatics, 9(499), 2008.
15. M. Rocha, R. Mendes, P. Maia, D. Glez-Pena, and F. Fdez-Riverola. A platform for the selection of genes in dna microarray data using evolutionary algorithms. In Proceedings of Genetic and Evolutionary Computation Conference (GECCO 2007), London, pages 415-421, 2007.
16. M. Rocha, J. Pinto, I. Rocha, and E. Ferreira. Evaluating evolutionary algorithms and differential evolution for the online optimization of fermentation processes. In Lecture Notes in Computer Science 4447, Proc. EvoBio2007, Valencia, pages 236-246, 2007.
17. M. Rocha, P. Sousa, P. Cortez, and M. Rio. Multiconstrained Optimization of Networks with Multicast and Unicast Traffic. In G. P. el al., editor, 11th IFIP/IEEE International Conference on Management of Multimedia and Mobile Networks and Services (MMNS 2008), volume 5274 of Lecture Notes in Computer Science, pages 139-150, Samos Island, Greece, sep 2008. Springer.
18. H.-P. Schwefel. Numerical Optimization of Computer Models. Wiley, 1981.
19. P. Sousa, M. Rocha, M. Rio, and P. Cortez. Efficient OSPF Weight Allocation for Intra-domain QoS Optimization. In Lecture Notes in Computer Science 4268, 16. Autonomic Principles of IP Operations and Management, pages 37-48. Springer, 2006.
20. P. Sousa, M. Rocha, M. Rio, and P. Cortez. Class-Based OSPF Traffic Engineering Inspired on Evolutionary Computation. In 5th International Conference on Wired/Wireless Internet Communications, Coimbra, Portugal, May 2007. Lecture Notes Computer Science, pages 141-152. Spriner-Verlag, 2007.
21. R. Storn and K. Price. Differential Evolution - a Simple and Efficient Heuristic for Global Optimization over Continuous Spaces. Journal of Global Optimization, 11:341-359, 1997.
22. I. H. Witten and E. Frank. Data Mining: Practical machine learning tools and techniques. Morgan Kaufman, 2005.
23. E. Zitzler, M. Laumanns, L. Thiele, et al. SPEA2: Improving the Strength Pareto Evolutionary Algorithm. EUROGEN, pages 95-100, 2001.