Gravitational interactions optimization

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6683 LNCS, Issue , 2011, Pages 226-237

  Flores, Juan J ^a   Lopez, Rodrigo ^a   Barrera, Julio ^b  

^a UNIVERSIDAD MICHOACANA DE SAN NICOLÁS DE HIDALGO   (Mexico)

^b DEPARTAMENTO DE FÍSICA   (Mexico)

Author keywords

Evolutionary computation; Gravitational interactions; Metaheuristic; Optimization

Indexed keywords

ANT COLONY OPTIMIZATION (ACO); EVOLUTIONARY STRATEGIES; GRAVITATIONAL FORCES; GRAVITATIONAL INTERACTION; META HEURISTICS; METAHEURISTIC; MULTI MODAL FUNCTION; MULTIMODAL PROBLEMS; OPTIMIZATION METAHEURISTIC; UNIMODAL;

ARTIFICIAL INTELLIGENCE; EVOLUTIONARY ALGORITHMS; GRAVITATION; HEURISTIC ALGORITHMS; OPTIMIZATION;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 84868586660     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-25566-3_17     Document Type: Conference Paper

References (12)

1. Barrera, J., Coello Coello, C.A.: A particle swarm optimization method for mul-timodal optimization based on electrostatic interaction. In: Aguirre, A.H., Borja, R.M., Garciá, C.A.R. (eds.) MICAI 2009. LNCS, Vol. 5845, pp. 622-632. Springer, Heidelberg (2009)
2. Colorni, A., Dorigo, M., Maniezzo, V.: Distributed optimization by ant colonies. In: Proceedings of the Parallel Problem Solving from Nature Conference. Elsevier Publishing, Amsterdam (1992)
3. Flores, J.J., Farías, R.L., Barrera, J.: Particle swarm optimization with gravitational interactions for multimodal and unimodal problems. In: Sidorov, G., Hernández Aguirre, A., Reyes García, C.A. (eds.) MICAI 2010, Part II. LNCS, Vol. 6438, pp. 361-370. Springer, Heidelberg (2010)
4. Goldberg, D.E.: Genetic Algorithms in Search, Optimization, and Machine Learning, 1st edn. Addison-Wesley Professional, Reading (1989)
5. Ingo, R.: Evolutionsstrategie 1994. PhD thesis, Technische Universität Berlin (1994)
6. Kennedy, J., Eberhart, R.: Swarm Intelligence. In: Evolutionary Computation. Morgan Kaufmann Publisher, San Francisco (2001)
7. Li, X.: A multimodal particle swarm optimizer based on fitness euclidean-distance ratio. In: Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation (GECCO 2007), pp. 78-85. ACM, New York (2007)
8. Newton, I.: Newtons Principia Mathematica. Física. Ediciones Altaya, S.A., 21 edition (1968)
9. Parsopoulos, K.E., Magoulas, G.D., Uxbridge, U.P., Vrahatis, M.N., Plagianakos, V.P.: Stretching technique for obtaining global minimizers through particle swarm optimization. In: Proceedings of the Particle Swarm Optimization Workshop, pp. 22-29 (2001)
10. Parsopoulos, K.E., Plagianakos, V.P., Magoulas, G.D., Vrahatis, M.N.: Improving the particle swarm optimizer by function "stretching,". Nonconvex Optimization and its Applications 54, 445-458 (2001)
11. Rashedi, E., Nezamabadi-pour, H., Saryazdi, S.: Gsa: A gravitational search algorithm. Information Sciences 179(13), 2232-2248 (2009)
12. Robert, H., David, R.: Physics Part I. Physics (1966)