Keyword

hypervolume indicator

Description: The hypervolume indicator is a measure in multiobjective optimization that quantifies the objective-space volume dominated by a solution set relative to a reference point.

Primary topic: Advanced Multi-Objective Optimization Algorithms (58%)

OpenAlex ID: keywords/hypervolume-indicator

HypE: An Algorithm for Fast Hypervolume-Based Many-Objective Optimization

2010 · Johannes Bader, Eckart Zitzler · Evolutionary Computation · 2,081

The Hypervolume Indicator Revisited: On the Design of Pareto-compliant Indicators Via Weighted Integration

2007 · Eckart Zitzler, Dimo Brockhoff, et al. · Springer eBooks · 594

An Improved Dimension-Sweep Algorithm for the Hypervolume Indicator

2006 · C.M. Fonseca, L. Paquete, et al. · 527

The bi-objective Pollution-Routing Problem

2013 · Emrah Demir, Tolga Bektaş, et al. · European Journal of Operational Research · 460

A Fast Way of Calculating Exact Hypervolumes

2011 · Lyndon While, Lucas Bradstreet, et al. · IEEE Transactions on Evolutionary Computation · 455

A Survey on the Hypervolume Indicator in Evolutionary Multiobjective Optimization

2020 · Ke Shang, Hisao Ishibuchi, et al. · IEEE Transactions on Evolutionary Computation · 384

Theory of the hypervolume indicator

2009 · Anne Auger, Johannes Bader, et al. · 377

Optimized sizing of a standalone PV-wind-hydropower station with pumped-storage installation hybrid energy system

2019 · Xiao Xu, Weihao Hu, et al. · Renewable Energy · 337

Comparing state-of-the-art evolutionary multi-objective algorithms for long-term groundwater monitoring design

2005 · J.B. Kollat, P.M. Reed · Advances in Water Resources · 329

The Hypervolume Indicator

2021 · Andreia P. Guerreiro, Carlos M. Fonseca, et al. · ACM Computing Surveys · 317

PDF

On the Complexity of Computing the Hypervolume Indicator

2009 · N. Beume, C.M. Fonseca, et al. · IEEE Transactions on Evolutionary Computation · 312

PDF

Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm

2018 · Eric Bradford, Artur M. Schweidtmann, et al. · Journal of Global Optimization · 266

A Simple and Fast Hypervolume Indicator-Based Multiobjective Evolutionary Algorithm

2014 · Siwei Jiang, Jie Zhang, et al. · IEEE Transactions on Cybernetics · 261

How to Specify a Reference Point in Hypervolume Calculation for Fair Performance Comparison

2018 · Hisao Ishibuchi, Ryo Imada, et al. · Evolutionary Computation · 238

Hypervolume-based expected improvement: Monotonicity properties and exact computation

2011 · Michael T. M. Emmerich, Andre H. Deutz, et al. · 215

Neural network based multi-objective evolutionary algorithm for dynamic workflow scheduling in cloud computing

2019 · Goshgar Ismayilov, Haluk Rahmi Topcuoglu · Future Generation Computer Systems · 193

On the properties of the R2 indicator

2012 · Dimo Brockhoff, Tobias Wagner, et al. · Genetic and Evolutionary Computation Conference (GECCO) · 178

Multi-objective optimization of energy performance for a detached residential building with a sunspace using the NSGA-II genetic algorithm

2021 · Ana Vukadinović, Jasmina Radosavljević, et al. · Solar Energy · 172

Improved many-objective particle swarm optimization algorithm for scientific workflow scheduling in cloud computing

2020 · Sahar Saeedi, Reihaneh Khorsand, et al. · Computers & Industrial Engineering · 162

MOELS: Multiobjective Evolutionary List Scheduling for Cloud Workflows

2019 · Quanwang Wu, MengChu Zhou, et al. · IEEE Transactions on Automation Science and Engineering · 145

On using the hypervolume indicator to compare Pareto fronts: Applications to multi-criteria optimal experimental design

2015 · Yongtao Cao, Byran J. Smucker, et al. · Journal of Statistical Planning and Inference · 140

Faster Hypervolume-Based Search Using Monte Carlo Sampling

2009 · Johannes Bader, Kalyanmoy Deb, et al. · Lecture notes in economics and mathematical systems · 140

Improving hypervolume-based multiobjective evolutionary algorithms by using objective reduction methods

2007 · Dimo Brockhoff, Eckart Zitzler · IEEE Congress on Evolutionary Computation (CEC) · 137

A Study of Multiobjective Metaheuristics When Solving Parameter Scalable Problems

2010 · J J Durillo, A J Nebro, et al. · IEEE Transactions on Evolutionary Computation · 132

Comparison of Hypervolume, IGD and IGD+ from the Viewpoint of Optimal Distributions of Solutions

2019 · Hisao Ishibuchi, Ryo Imada, et al. · Lecture notes in computer science · 127

Works count: 1,040

Citation count: 19,980