Result 1 to 20 of 147 total
Optimal design of container inspection strategies considering multiple objectives via an evolutionary approach. (English)
Ann. Oper. Res. 196, 167-187 (2012).
1
An approach to instantly use single-objective results for multi-objective evolutionary combinatorial optimization. (English)
Hamadi, Youssef (ed.) et al., Learning and intelligent optimization. 6th international conference, LION 6, Paris, France, January 16‒20, 2012. Revised selected papers. Berlin: Springer (ISBN 978-3-642-34412-1/pbk). Lecture Notes in Computer Science 7219, 396-401 (2012).
2
Multiobjective dynamic multi-swarm particle swarm optimization for environmental/economic dispatch problem. (English)
Huang, De-Shuang (ed.) et al., Intelligent computing technology. 8th international conference, ICIC 2012, Huangshan, China, July 25‒29, 2012. Proceedings. Berlin: Springer (ISBN 978-3-642-31587-9/pbk). Lecture Notes in Computer Science 7389, 657-664 (2012).
3
Achieving balance between proximity and diversity in multi-objective evolutionary algorithm. (English)
Inf. Sci. 182, No. 1, 220-242 (2012).
4
A new mechanism to maintain diversity in multi-objective metaheuristics. (English)
Optimization 61, No. 7, 823-854 (2012).
5
An NSGA-II algorithm for the green vehicle routing problem. (English)
Hao, Jin-Kao (ed.) et al., Evolutionary computation in combinatorial optimization. 12th European conference, EvoCOP 2012, Málaga, Spain, April 11‒13, 2012. Proceedings. Berlin: Springer (ISBN 978-3-642-29123-4/pbk). Lecture Notes in Computer Science 7245, 37-48 (2012).
6
Optimizing energy consumption in heterogeneous wireless sensor networks by means of evolutionary algorithms. (English)
Di Chio, Cecilia (ed.) et al., Applications of evolutionary computation. EvoApplications 2012: EvoCOMNET, EvoCOMPLEX, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoNUM, EvoPAR, EvoRISK, EvoSTIM, and EvoSTOC, Málaga, Spain, April 11‒13, 2012. Proceedings. Berlin: Springer (ISBN 978-3-642-29177-7/pbk). Lecture Notes in Computer Science 7248, 1-10 (2012).
7
Convergence of set-based multi-objective optimization, indicators and deteriorative cycles. (English)
Theor. Comput. Sci. 456, 2-17 (2012).
8
Approximating the least hypervolume contributor: NP-hard in general, but fast in practice. (English)
Theor. Comput. Sci. 425, 104-116 (2012).
9
Improvement of dynamic multi-objective evolutionary and orthogonal test for four-branch satellite antenna. (Chinese)
J. Comput. Appl. 31, No. 10, 2880-2882 (2011).
10
Multi-objective optimization of constrained parallel hybrid electric vehicle based on SPEA2. (Chinese)
J. Comput. Appl. 31, No. 11, 3091-3093 (2011).
11
Evolutionary computation of multi-band antenna using multi-objective evolutionary algorithm based on decomposition. (English)
Liu, Baoxiang (ed.) et al., Information computing and applications. Second international conference, ICICA 2011, Qinhuangdao, China, October 28‒31, 2011. Proceedings. Berlin: Springer (ISBN 978-3-642-25254-9/pbk). Lecture Notes in Computer Science 7030, 383-390 (2011).
12
Convergence of multi-objective evolutionary algorithms to a uniformly distributed representation of the Pareto front. (English)
Inf. Sci. 181, No. 16, 3336-3355 (2011).
13
Multi-objective evolutionary optimizations of a space-based reconfigurable sensor network under hard constraints. (English)
Soft Comput. 15, No. 1, 25-36 (2011).
14
Searching for knee regions of the Pareto front using mobile reference points. (English)
Soft Comput. 15, No. 9, 1807-1823 (2011).
15
PITAGORAS-PSP: including domain knowledge in a multi-objective approach for protein structure prediction. (English)
Neurocomputing 74, No. 16, 2675-2682 (2011).
16
Learning in the feed-forward Random Neural Network: a critical review. (English)
Perform. Eval. 68, No. 4, 361-384 (2011).
17
Evolutionary algorithms for solving multi-objective travelling salesman problem. (English)
Flex. Serv. Manuf. J. 23, No. 2, 207-241 (2011).
18
A clustering-based niching framework for the approximation of equivalent Pareto-subsets. (English)
Int. J. Comput. Intell. Appl. 10, No. 3, 295-311 (2011).
19
Optimizing interval multi-objective problems using IEAs with preference direction. (English)
Lu, Bao-Liang (ed.) et al., Neural information processing. 18th international conference, ICONIP 2011, Shanghai, China, November 13‒17, 2011. Proceedings, Part II. Berlin: Springer (ISBN 978-3-642-24957-0/pbk). Lecture Notes in Computer Science 7063, 445-452 (2011).
20
Result 1 to 20 of 147 total
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