Evolutionary Computation Related Publication

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Technical Reports

Yang Yu, Chao Qian, and Zhi-Hua Zhou. Towards analyzing crossover operators in evolutionary search via general Markov chain switching theorem. CORR abs/1111.0907, 2011.

Journal Articles

Chao Qian, Yang Yu, and Zhi-Hua Zhou. Analyzing evolutionary optimization in noisy environments. Evolutionary Computation, 2016, in press. (Preprint PDF)

Chao Qian, Yang Yu, and Zhi-Hua Zhou. Variable solution structure can be helpful in evolutionary optimization. Science China: Information Sciences, 2016, in press. (Preprint PDF)

Yang Yu, Chao Qian, and Zhi-Hua Zhou. Switch analysis for running time analysis of evolutionary algorithms. IEEE Transactions on Evolutionary Computation, 2015, in press. (Preprint PDF)

Chaoli Sun, Yaochu Jin, Jianchao Zeng, and Yang Yu. A two-layer surrogate-assisted particle swarm optimization algorithm. Soft Computing,19(6):1461-1475, 2015.

Chao Qian, Yang Yu, and Zhi-Hua Zhou. An analysis on recombination in multi-objective evolutionary optimization. Artificial Intelligence, 2013, 204:99-119. (Extended from GECCO'11) (Preprint PDF)

Yang Yu, Xin Yao, and Zhi-Hua Zhou. On the approximation ability of evolutionary optimization with application to minimum set cover. Artificial Intelligence, 2012, 180-181:20-33. (Preprint PDF) (CORR abs/1011.4028)

Yang Yu and Zhi-Hua Zhou. A new approach to estimating the expected first hitting time of evolutionary algorithms. Artificial Intelligence, 2008, 172(15): 1809-1832. (Extended from AAAI'06) (Preprint PDF)

Conference Papers

Chao Qian, Yang Yu and Zhi-Hua Zhou. On constrained Boolean Pareto optimization. In: Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI'15), Buenos Aires, Argentina, 2015. (PDF)

Yang Yu, Chao Qian. Running time analysis: Convergence-based analysis reduces to switch analysis. In: Proceedings of the 2015 IEEE Congress on Evolutionary Computation (CEC'15), Sendai, Japan, 2015. (PDF)

Chao Qian, Yang Yu and Zhi-Hua Zhou. Pareto ensemble pruning. In: Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI'15), Austin, TX, 2015, pp.2935-2941.(PDF)

Chao Qian, Yang Yu, Yaochu Jin and Zhi-Hua Zhou. On the effectiveness of sampling for evolutionary optimization in noisy environments. In: Proceedings of the 13th International Conference on Parallel Problem Solving from Nature (PPSN’14), Ljubljana, Slovenia, 2014, pp.302-311. (PDF)

Yang Yu, and Hong Qian. The sampling-and-learning framework: A statistical view of evolutionary algorithms. In: Proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC'14), Beijing, China, 2014, pp.149-158. (PDF)

Yang Yu, Xin Yao, and Zhi-Hua Zhou. On the approximation ability of evolutionary optimization with application to minimum set cover: Extended abstract. In: Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI'13) (Journal Paper Track), Beijing, China, 2013.

Chao Qian, Yang Yu, and Zhi-Hua Zhou. On algorithm-dependent boundary case identification for problem classes. In: Proceedings of the 12th International Conference on Parallel Problem Solving from Nature (PPSN'12) Taormina, Italy, 2012, pp.62-71. (PDF)

Chao Qian, Yang Yu, and Zhi-Hua Zhou. An analysis on recombination in multi-objective evolutionary optimization. In: Proceedings of the 13th ACM Conference on Genetic and Evolutionary Computation (GECCO'11), Dublin, Ireland, 2011, pp. 2051-2058. (PDF) (This paper won the Best Paper Award of the Theory Track at GECCO'11)

Chao Qian, Yang Yu, and Zhi-Hua Zhou. Collisions are helpful for computing unique input-output sequences. In: Proceedings of the 13th ACM Conference on Genetic and Evolutionary Computation (GECCO'11) (Companion Material/Poster), Dublin, Ireland, 2011, pp. 265-266. (PDF)

Yang Yu, Chao Qian, and Zhi-Hua Zhou. Towards analyzing recombination operators in evolutionary search. In: Proceedings of the 11th International Conference on Parallel Problem Solving from Nature (PPSN'10) Part I, Krakow, Poland, 2010, pp.144-153. (PDF)

Yang Yu and Zhi-Hua Zhou. On the usefulness of infeasible solutions in evolutionary search: A theoretical study. In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC'08), Hong Kong, China, 2008, pp.835-840. (PDF)

Yang Yu and Zhi-Hua Zhou. A new approach to estimating the expected first hitting time of evolutionary algorithms. In: Proceedings of the 21st National Conference on Artificial Intelligence (AAAI'06), Boston, MA, 2006, pp.555-560. (PDF)

Thesis

Yang Yu. Evolutionary Computation: Theoretical Analysis and Learning Algorithms. Ph.D. Dissertation, 2011.