EMODS: A NOVEL EVOLUTIONARY METAHEURISTIC BASED IN THE AUTOMATA THEORY FOR THE MULTIOBJECTIVE OPTIMIZATION OF COMBINATORIALS PROBLEMS
Elias David Nino Ruiz, Anangelica Isabel Chinchilla Camargo
2012
Abstract
This paper states a novel Evolutionary Metaheuristic based in the Automata Theory for the Multiobjective Optimization of Combinatorial Problems named EMODS. The proposed algorithm uses the natural selection theory to explore the feasible solutions space of a Combinatorial Problem. Due to this, local optimums are avoided. Also, EMODS takes advantage in the optimization process from the Metaheuristic of Deterministic Swapping to avoid finding unfeasible solutions. The proposed algorithm was tested using well known instances from the TSPLIB with three objectives. Its results were compared against four Multiobjective Simulated Annealing inspired Algorithms using metrics from the specialized literature. In every case, the EMODS results on the metrics were always better and in some of those cases, the distance from the Real Solutions was 4%.
References
- Fung, R., Tang, J., and Zhang, J. (2009). A multi-depot vehicle routing problem with weight-related costs. In Computers Industrial Engineering, 2009. CIE 2009. International Conference on, pages 1028 -1033.
- Glover, F. and Laguna, M. (1997). Tabu Search. Kluwer Academic Publishers, Norwell, MA, USA.
- Heidelberg, U. O. Tsplib - office research group discrete optimization - university of heidelberg. http:// comopt.ifi.uni-heidelberg.de/software/TSPLIB95/.
- Hu, B. and Raidl, G. (2008). Solving the railway traveling salesman problem via a transformation into the classical traveling salesman problem. In Hybrid Intelligent Systems, 2008. HIS 7808. Eighth International Conference on, pages 73 -77.
- Jingyu, Y., Chongguo, L., Zhi, W., Lei, D., and Demin, S. (2007). Diversity metrics in multi-objective optimization: Review and perspective. In Integration Technology, 2007. ICIT 07. IEEE International Conference on, pages 553-557.
- Li, H. and Landa-Silva, D. (2008). Evolutionary multiobjective simulated annealing with adaptive and competitive search direction. In Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on, pages 3311 -3318.
- Lim, A. and Wang, F. (2005). Multi-depot vehicle routing problem: a one-stage approach. Automation Science and Engineering, IEEE Transactions on, 2(4):397 - 402.
- Nin˜o, E. D., Ardila, C., Donoso, Y., and Jabba, D. (2010). A novel algorithm based on deterministic finite automaton for solving the mono-objective symmetric traveling salesman problem. International Journal of Artificial Intelligence, 5(A10):101 - 108.
- Nin˜o, E. D., Ardila, C., Donoso, Y., Jabba, D., and Barrios, A. (2011). Mods: A novel metaheuristic of deterministic swapping for the multi objective optimization of combinatorials problems. Computer Technology and Application, 2(4):280 - 292.
- Oberlin, P., Rathinam, S., and Darbha, S. (2009). A transformation for a heterogeneous, multiple depot, multiple traveling salesman problem. In American Control Conference, 2009. ACC 7809., pages 1292 -1297.
- Pretorius, W. and Helberg, A. (2004). Application of an adapted evaluation process using numerical amp; qualitative weighted sum techniques. In AFRICON, 2004. 7th AFRICON Conference in Africa, volume 1, pages 367 -372 Vol.1.
- Sauer, J. and Coelho, L. (2008). Discrete differential evolution with local search to solve the traveling salesman problem: Fundamentals and case studies. In Cybernetic Intelligent Systems, 2008. CIS 2008. 7th IEEE International Conference on, pages 1 -6.
- Wang, S.-Q. and Xu, Z.-Y. (2009). Ant colony algorithm approach for solving traveling salesman with multiagent. In Information Engineering, 2009. ICIE 7809. WASE International Conference on, volume 1, pages 381 -384.
- Wang, Y. and Lang, M. (2008). Study on the model and tabu search algorithm for delivery and pickup vehicle routing problem with time windows. In Service Operations and Logistics, and Informatics, 2008. IEEE/SOLI 2008. IEEE International Conference on, volume 1, pages 1464 -1469.
- Yong-fa, Q. and Ming-yang, Z. (2004). Research on a new multiobjective combinatorial optimization algorithm. In Robotics and Biomimetics, 2004. ROBIO 2004. IEEE International Conference on, pages 187 -191.
Paper Citation
in Harvard Style
Nino Ruiz E. and Chinchilla Camargo A. (2012). EMODS: A NOVEL EVOLUTIONARY METAHEURISTIC BASED IN THE AUTOMATA THEORY FOR THE MULTIOBJECTIVE OPTIMIZATION OF COMBINATORIALS PROBLEMS . In Proceedings of the 1st International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-8425-97-3, pages 399-404. DOI: 10.5220/0003754003990404
in Bibtex Style
@conference{icores12,
author={Elias David Nino Ruiz and Anangelica Isabel Chinchilla Camargo},
title={EMODS: A NOVEL EVOLUTIONARY METAHEURISTIC BASED IN THE AUTOMATA THEORY FOR THE MULTIOBJECTIVE OPTIMIZATION OF COMBINATORIALS PROBLEMS},
booktitle={Proceedings of the 1st International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},
year={2012},
pages={399-404},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003754003990404},
isbn={978-989-8425-97-3},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 1st International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - EMODS: A NOVEL EVOLUTIONARY METAHEURISTIC BASED IN THE AUTOMATA THEORY FOR THE MULTIOBJECTIVE OPTIMIZATION OF COMBINATORIALS PROBLEMS
SN - 978-989-8425-97-3
AU - Nino Ruiz E.
AU - Chinchilla Camargo A.
PY - 2012
SP - 399
EP - 404
DO - 10.5220/0003754003990404