A framework of quantum-inspired multi-objective evolutionary algorithms and its convergence condition

Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference

Volumn , Issue , 2007, Pages 908-

  Li, Zhiyong ^a   Rudolph, Guenter ^b  

^a HUNAN UNIVERSITY   (China)

^b TU DORTMUND UNIVERSITY   (Germany)

Author keywords

Multi objective evolutionary algorithms; Pareto optimal set; Quantum computing; Stochastic convergence

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; EVOLUTIONARY ALGORITHMS; PARETO PRINCIPLE; QUANTUM COMPUTERS; STOCHASTIC MODELS;

CONVERGENCE CONDITIONS; PARETO OPTIMAL SETS; STOCHASTIC CONVERGENCE;

MULTIOBJECTIVE OPTIMIZATION;

EID: 34548083517     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1276958.1277138     Document Type: Conference Paper

References (4)

1. Rudolph, G., and Agapie, A. Convergence Properties of Some Multi-Objective Evolutionary Algorithms, in the 2000 Congress on Evolutionary Computation (CEC 2000). 2000. Piscataway (NJ): IEEE Press.
2. Hanne, T. A multiobjective evolutionary algorithm for approximating the efficient set. European Journal of Operational Research, 2007. 176: p. 1723-1734.
3. Kim, Y., Kim, J.-H., and Han, K.-H. Quantum-inspired Multiobjective Evolutionary Algorithm for Multiobjective 0/1 Knapsack Problems, in 2006 IEEE Congress on Evolutionary Computation. 2006. Canada: IEEE Press.
4. Li, Z., and Rudolph, G. A Framework of Quantum-inspired Multi-Objective Evolutionary Algorithms and its Convergence Properties. Technical Report CI228/07, SFB 531, Universität Dortmund, 2007.