Results 191 to 200 of about 28,586 (232)

Improving NSGA-II for Multi-Constrained QoS Routing

Journal of Circuits, Systems and Computers, 2021
With the development of 5G technology, the traffics which need multiple quality of service (QoS) constraints greatly increase. The existing QoS routing algorithms either support a single QoS constraint or support multiple constraints are mixed with fixed weights. The latter is essentially a single-constrained QoS algorithm. Few studies can provide the
Xin Liu 0081, Jingyuan Zhao, Lin Zheng, Liying Li, Li Liu, Penglong Jiao, Yao Liu 0017   +6 more
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Parallelization and Optimization of NSGA-II on Sunway TaihuLight System

IEEE Transactions on Parallel and Distributed Systems, 2021
Sunway TaihuLight system is the first supercomputer offering a peak performance over 100 PFlops, which can be utilized to parallelize Non-dominated Sorting Genetic Algorithm II (NSGA-II), a standard approach to multi-objective optimization. However, insufficient off-chip memory bandwidth and limited scratchpad memory capacity of the supercomputer ...
Xin Liu 0081, Jun Sun, Lin Zheng, Su Wang 0005, Yao Liu 0017, Tongquan Wei   +5 more
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Who's better? PESA or NSGA II?

Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007), 2007
According to the no free lunch (NFL) theorems all black-box algorithms perform equally well when compared over the entire set of optimization problems. An important problem related to NFL is finding a test problem for which a given algorithm is better than another given algorithm.
Laura Diosan, Mihai Oltean
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Applying NSGA-II for Solving the Ontology Alignment Problem

2013 IEEE International Conference on Systems, Man, and Cybernetics, 2013
Achieving semantic interoperability is an essential task for all distributed and open knowledge based systems. Currently, the best technology recognized for fulfilling this complex task is represented by ontologies. Unfortunately, in turn, the power of ontological representation is reduced by the semantic heterogeneity problem which affects two ...
Giovanni Acampora, Uzay Kaymak, Vincenzo Loia, Autilia Vitiello   +3 more
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Multi-objective Feature Selection with NSGA II

2007
This paper deals with the multi-objective definition of the feature selection problem for different pattern recognition domains. We use NSGA II the latest multi-objective algorithm developed for resolving problems of multi-objective aspects with more accuracy and a high convergence speed.
Tarek M. Hamdani, Jin-Myung Won, Adel M. Alimi, Fakhri Karray   +3 more
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A Hybrid NSGA-II for Matching Biomedical Ontology

2018
Over the recent years, ontologies are widely used in the biomedical domains. However, biomedical ontology heterogeneity problem hamper the cooperation between intelligent applications based on biomedical ontologies. It is crucial to establish correspondences between the heterogeneous biomedical concepts in different ontologies, which is so-called ...
Xingsi Xue, Jie Chen, Junfeng Chen, Dongxu Chen   +3 more
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Alleviate the Hypervolume Degeneration Problem of NSGA-II

2011
A number of multiobjective evolutionary algorithms, together with numerous performance measures, have been proposed during past decades. One measure that has been popular recently is the hypervolume measure, which has several theoretical advantages. However, the well-known nondominated sorting genetic algorithm II (NSGA-II) shows a fluctuation or even ...
Fei Peng, Ke Tang 0001
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Ontology alignment based on instance using NSGA-II

Journal of Information Science, 2014
Nowadays, ontologies are widely used to solve data heterogeneity problems on the Semantic Web. However, simple use of these ontologies may raise the heterogeneity problem to a higher level. Addressing this problem requires identification of correspondences between the entities of various ontologies.
Xingsi Xue, Yuping Wang 0003
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Ranking Center-based NSGA-II

2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2023
Rasa Khosrowshahli, Shahryar Rahnamayan, Amin Ibrahim, Masoud Makrehchi   +3 more
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AP-NSGA-II: An Evolutionary Multi-objective Optimization Algorithm Using Average-Point-Based NSGA-II

2014
Multi-objective optimization involves optimizing a number of objectives simultaneously, and it becomes challenging when the objectives conflict each other, i.e., the optimal solution of one objective function is different from that of other. These problems give rise to a set of trade-off optimal solutions, popularly known as Pareto-optimal solution ...
Prabhujit Mohapatra, Santanu Roy
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