Ryo Imada

According to our database1, Ryo Imada authored at least 11 papers between 2016 and 2019.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2019
Comparison of Hypervolume, IGD and IGD+ from the Viewpoint of Optimal Distributions of Solutions.
Proceedings of the Evolutionary Multi-Criterion Optimization, 2019

Two-Layered Weight Vector Specification in Decomposition-Based Multi-Objective Algorithms for Many-Objective Optimization Problems.
Proceedings of the IEEE Congress on Evolutionary Computation, 2019

2018
Reference Point Specification in Inverted Generational Distance for Triangular Linear Pareto Front.
IEEE Trans. Evolutionary Computation, 2018

How to Specify a Reference Point in Hypervolume Calculation for Fair Performance Comparison.
Evolutionary Computation, 2018

Use of Two Reference Points in Hypervolume-Based Evolutionary Multiobjective Optimization Algorithms.
Proceedings of the Parallel Problem Solving from Nature - PPSN XV, 2018

Dynamic Specification of a Reference Point for Hypervolume Calculation in SMS-EMOA.
Proceedings of the 2018 IEEE Congress on Evolutionary Computation, 2018

2017
Use of inverted triangular weight vectors in decomposition-based multiobjective algorithms.
Proceedings of the 2017 IEEE International Conference on Systems, Man, and Cybernetics, 2017

Use of Inverted Triangular Weight Vectors in Decomposition-Based Many-Objective Algorithms.
Proceedings of the Simulated Evolution and Learning - 11th International Conference, 2017

Reference point specification in hypervolume calculation for fair comparison and efficient search.
Proceedings of the Genetic and Evolutionary Computation Conference, 2017

Hypervolume Subset Selection for Triangular and Inverted Triangular Pareto Fronts of Three-Objective Problems.
Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2017

2016
Performance comparison of NSGA-II and NSGA-III on various many-objective test problems.
Proceedings of the IEEE Congress on Evolutionary Computation, 2016


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