Results 11 to 20 of about 8,528 (188)
The Hypervolume Indicator [PDF]
ACM Computing Surveys, 2021 The hypervolume indicator is one of the most used set-quality indicators for the assessment of stochastic multiobjective optimizers, as well as for selection in evolutionary multiobjective optimization algorithms. Its theoretical properties justify its wide acceptance, particularly the strict monotonicity with respect to set dominance, which is still ...
Andreia P. Guerreiro +2 more
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Scattering hypervolume of spin-polarized fermions [PDF]
Physical Review A, 2021 15 pages, 3 ...
Zipeng Wang, Shina Tan
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R2-Based Hypervolume Contribution Approximation [PDF]
IEEE Transactions on Evolutionary Computation, 2020 In this letter, a new hypervolume contribution approximation method is proposed which is formulated as an R2 indicator. The basic idea of the proposed method is to use different line segments only in the hypervolume contribution region for the hypervolume contribution approximation. Comparing with a traditional method which is based on the R2 indicator
Ke Shang, Hisao Ishibuchi, Xizi Ni
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Hypervolume visualization [PDF]
Proceedings of the 1998 IEEE symposium on Volume visualization, 1998 Hypervolume visualization is designed to provide simple and fully explanatory images that give comprehensive in-sights into the global structure of scalar fields of any dimension. The basic idea is to have a dimension independent viewing system that scales nicely with the geometric dimension of the dataset and that can be combined with classical ...
Bajaj, C. L. +3 more
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Frontiers in Veterinary Science, 2021 Many infectious diseases in wildlife occur under quantifiable landscape ecological patterns useful in facilitating epidemiological surveillance and management, though little is known about prion diseases.
Steven N. Winter +5 more
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A Simplified Hypervolume-Based Evolutionary Algorithm for Many-Objective Optimization
Complexity, 2020 Evolutionary algorithms based on hypervolume have demonstrated good performance for solving many-objective optimization problems. However, hypervolume needs prohibitively expensive computational effort.
Hong Ji, Cai Dai
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Improved Lebesgue Indicator-Based Evolutionary Algorithm: Reducing Hypervolume Computations
Mathematics, 2021 One of the major limitations of evolutionary algorithms based on the Lebesgue measure for multi-objective optimization is the computational cost required to approximate the Pareto front of a problem.
Saúl Zapotecas-Martínez +2 more
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Ecological Indicators, 2022 Species’ vulnerability to climate change is often assessed by focusing on potential changes of species’ ranges. This study aimed to develop community-level vulnerability indices which measure bryophyte community vulnerability to climate change, based on ...
H. Hespanhol +4 more
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A Two-Archive Harris Hawk Optimization for Solving Many-Objective Optimal Power Flow Problems
IEEE Access, 2023 To improve power system operation and management and accomplish modern power system requirements, a new algorithm named two-archive harris hawk optimization (TwoArchHHO) is proposed to solve many-objective optimal power flow (MaOOPF) problems in this ...
Sirote Khunkitti +2 more
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Multiplicative Approximations, Optimal Hypervolume Distributions, and the Choice of the Reference Point [PDF]
, 2013 Many optimization problems arising in applications have to consider several objective functions at the same time. Evolutionary algorithms seem to be a very natural choice for dealing with multi-objective problems as the population of such an algorithm ...
Friedrich, Tobias +2 more
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