M. Munetomo

发表

MHGrid: Towards an Ideal Optimization Environment for Global Optimization Problems Using Grid Computing

Asim Munawar, Mohamed Wahib, Masaharu Munetomo, 2007, Eighth International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT 2007).

Towards a User Deployable Service-oriented Autonomic Multi-cloud Overlay Infrastructure for Sky Computing

C. Powell, M. Munetomo, Takashi Aizawa, 2013 .

Dynamical intervention planning against COVID-19-like epidemics

A. Scala, M. Schlueter, G. Oliva, 2022, PloS one.

Designing a distributed algorithm for bandwidth allocation with a genetic algorithm

Masaharu Munetomo, Kiyoshi Akama, Yoshiharu Sato, 2004, Systems and Computers in Japan.

Considering ECGA which Introduces Tabu Search

Masaharu Munetomo, Kiyoshi Akama, Yuta Satake, 2006 .

An Intelligent Network Routing Algorithm by a Genetic Algorithm

Masaharu Munetomo, Yoshiaki Takai, Yoshiharu Sato, 1997, ICONIP.

Screening for FtsZ Dimerization Inhibitors Using Fluorescence Cross-Correlation Spectroscopy and Surface Resonance Plasmon Analysis

M. Kinjo, A. Sasaki, S. Mikuni, 2015, PloS one.

Cooperative coevolutionary hybrid NSGA-II with Linkage Measurement Minimization for Large-scale Multi-objective optimization

M. Munetomo, Rui Zhong, 2022, 2208.13415.

Accelerating the Evolutionary Algorithms by Gaussian Process Regression with ε-greedy acquisition function

M. Munetomo, Rui Zhong, En-zhan Zhang, 2022, ArXiv.

Accelerating the Genetic Algorithm for Large-scale Traveling Salesman Problems by Cooperative Coevolutionary Pointer Network with Reinforcement Learning

M. Munetomo, Rui Zhong, En-zhan Zhang, 2022, ArXiv.

Optimal answer generation by equivalent transformation incorporating multi-objective genetic algorithm

C. Powell, M. Munetomo, K. Miura, 2022, Soft Comput..

Optimal answer generation by equivalent transformation incorporating multi-objective genetic algorithm

C. Powell, M. Munetomo, K. Miura, 2022, Soft Computing.

StGA: An application of a genetic algorithm to stochastic learning automata

Masaharu Munetomo, Yoshiharu Sato, Yoshiaki Takai, 1996, Systems and Computers in Japan.

Towards Thought Control of Next-Generation Wearable Computing Devices

Masaharu Munetomo, Courtney Powell, Masataka Mizukoshi, 2013, Brain and Health Informatics.

Network Structural Vulnerability: A Multiobjective Attacker Perspective

Masaharu Munetomo, Stefano Panzieri, Federica Pascucci, 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

A GPU Accelerated Fragment-based De Novo Ligand Design by a Bayesian Optimization Algorithm

Asim Munawar, Mohamed Wahib, Masaharu Munetomo, 2012 .

A Bayesian Optimization Algorithm for De Novo ligand design based docking running over GPU

Asim Munawar, Mohamed Wahib, Masaharu Munetomo, 2010, IEEE Congress on Evolutionary Computation.

The design, usage, and performance of GridUFO: A Grid based Unified Framework for Optimization

Asim Munawar, Mohamed Wahib, Masaharu Munetomo, 2010, Future Gener. Comput. Syst..

EA-based Problem Solving Environment over the GRID

Asim Munawar, Mohamed Wahib, Masaharu Munetomo, 2008 .

A Survey: Genetic Algorithms and the Fast Evolving World of Parallel Computing

Asim Munawar, Mohamed Wahib, Masaharu Munetomo, 2008, 2008 10th IEEE International Conference on High Performance Computing and Communications.

Parallel GEAs with Linkage Analysis over Grid

Asim Munawar, Mohamed Wahib, Masaharu Munetomo, 2008, Linkage in Evolutionary Computation.

Optimization problem solving framework employing GAs with linkage identification over a grid environment

Asim Munawar, Masaharu Munetomo, Kiyoshi Akama, 2007, 2007 IEEE Congress on Evolutionary Computation.

A Framework of GRID Problem-Solving Environment Employing Robust Evolutionary Search

Asim Munawar, Masaharu Munetomo, Kiyoshi Akama, 2007, EUROCAST.

An adaptive parameter binary-real coded genetic algorithm for constraint optimization problems: Performance analysis and estimation of optimal control parameters

Masaharu Munetomo, Kiyoshi Akama, Omar Abdul-Rahman, 2013, Inf. Sci..

Many-Constraint and Many-Objective optimization with Bias Index for Intercloud Multi-Workflow Resource Provisioning

C. Powell, M. Munetomo, K. Miura, 2022, 2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS).

Constrained Multi-objective Optimization Method for Practical Scientific Workflow Resource Selection

Masaharu Munetomo, Katsunori Miura, Courtney Powell, 2019, EMO.

Optimal and Feasible Cloud Resource Configurations Generation Method for Genomic Analytics Applications

Masaharu Munetomo, Katsunori Miura, Courtney Powell, 2018, 2018 IEEE International Conference on Cloud Computing Technology and Science (CloudCom).

Intercloud brokerages based on PLS method for deploying infrastructures for big data analytics

Masaharu Munetomo, Katsunori Miura, Courtney Powell, 2016, 2016 IEEE International Conference on Big Data (Big Data).

Toward a Genetic Algorithm Based Flexible Approach for the Management of Virtualized Application Environments in Cloud Platforms

Masaharu Munetomo, Omar Abdul-Rahman, Kiyoshi Akama, 2012, 2012 21st International Conference on Computer Communications and Networks (ICCCN).

An adaptive Parameters Binary-Real Coded Genetic Algorithm for Real Parameter Optimization: Performance Analysis and Estimation of Optimal Control Parameters

Masaharu Munetomo, Kiyoshi Akama, K. Akama, 2012 .

An adaptive resolution hybrid binary-real coded genetic algorithm

Masaharu Munetomo, Kiyoshi Akama, Omar Arif Abdul-Rahman, 2011, Artificial Life and Robotics.

An improved binary-real coded genetic algorithm for real parameter optimization

Masaharu Munetomo, Omar Abdul-Rahman, Kiyoshi Akama, 2011, 2011 Third World Congress on Nature and Biologically Inspired Computing.

GTOPX Space Mission Benchmarks pdf

Mohamed Wahib, Masaharu Munetomo, Markus Wagner, 2020, SoftwareX.

New State-of-the-Art Results on ESA’s Messenger Space Mission Benchmark

M. Wahib, M. Schlueter, M. Munetomo, 2021 .

Numerical Optimization of ESA's Messenger Space Mission Benchmark

Mohamed Wahib, Masaharu Munetomo, Martin Schlueter, 2017, EvoApplications.

MIDACO Parallelization Scalability on 200 MINLP Benchmarks

Masaharu Munetomo, Martin Schlueter, M. Schlueter, 2017, J. Artif. Intell. Soft Comput. Res..

Numerical assessment of the parallelization scalability on 200 MINLP benchmarks

Masaharu Munetomo, Martin Schlueter, M. Schlueter, 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

Parallelization strategies for evolutionary algorithms for MINLP

Masaharu Munetomo, Martin Schlueter, M. Schlueter, 2013, 2013 IEEE Congress on Evolutionary Computation.

Linkage Identification by Nonlinearity Check for Real-Coded Genetic Algorithms

Masaharu Munetomo, Kiyoshi Akama, Masaru Tezuka, 2004, GECCO.

A genetic approach to dynamic load balancing in a distributed computing system

Masaharu Munetomo, Yoshiaki Takai, Yoshiharu Sato, 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

A migration scheme for the genetic adaptive routing algorithm

Masaharu Munetomo, Yoshiaki Takai, Yoshiharu Sato, 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

Development of a multi-player interactive genetic algorithm-based 3D modeling system for glasses

Masaharu Munetomo, Takahito Seyama, M. Munetomo, 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

Scalable 3 D Modeling Using Multi-player Interactive Genetic Algorithm on Cloud Platform as a Service

Masaharu Munetomo, Shintaro Bando, Takahito Seyama, 2014 .

Linkage Identification by Fitness Difference Clustering

Masaharu Munetomo, Miwako Tsuji, Kiyoshi Akama, 2006, Evolutionary Computation.

Modeling Dependencies of Loci with String Classification According to Fitness Differences

Masaharu Munetomo, Kiyoshi Akama, Miwako Tsuji, 2004, GECCO.

Linkage Identification by Non-monotonicity Detection for Overlapping Functions

David E. Goldberg, Masaharu Munetomo, D. Goldberg, 1999, Evolutionary Computation.

An Adaptive Network Routing Algorithm Employing Path Genetic Operators

Masaharu Munetomo, Yoshiaki Takai, Yoshiharu Sato, 1997, ICGA.

Hybrid of genetic algorithm and local search to solve MAX-SAT problem using nVidia CUDA framework

Asim Munawar, Mohamed Wahib, Masaharu Munetomo, 2009, Genetic Programming and Evolvable Machines.

Optimization of parallel Genetic Algorithms for nVidia GPUs

Asim Munawar, Mohamed Wahib, Masaharu Munetomo, 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).

Cooperative coevolutionary differential evolution with linkage measurement minimization for large-scale optimization problems in noisy environments

M. Munetomo, Rui Zhong, En-zhan Zhang, 2023, Complex & Intelligent Systems.

An Efficient Migration Scheme for Subpopulation-Based Asynchronously Parallel Genetic Algorithms

Masaharu Munetomo, Yoshiaki Takai, Yoshiharu Sato, 1993, ICGA.

A proposal for Zoning Crossover of Hybrid Genetic Algorithms for large-scale traveling salesman problems

Moritoshi Yasunaga, Kunihito Yamamori, Ikuo Yoshihara, 2010, IEEE Congress on Evolutionary Computation.

Generating collective behavior of a multi-legged robotic swarm using an evolutionary robotics approach

K. Ohkura, D. Morimoto, M. Munetomo, 2022, Artificial Life and Robotics.

Evolving collective step-climbing behavior in multi-legged robotic swarm

K. Ohkura, M. Munetomo, Motoaki Hiraga, 2022, Artificial Life and Robotics.

Cooperative coevolutionary Modified Differential Evolution with Distance-based Selection for Large-Scale Optimization Problems in noisy environments through an automatic Random Grouping

M. Munetomo, Rui Zhong, 2022, ArXiv.

Cooperative coevolutionary Modiﬁed Di ﬀ erential Evolution with Distance-based Selection for Large-Scale Optimization Problems through an automatic Random Grouping

M. Munetomo, Rui Zhong, 2022 .

Genetic Algorithm to Optimize Fitness Function with Sampling Error and its Application to Financial Optimization Problem

Masaharu Munetomo, Kiyoshi Akama, Masahiro Hiji, 2006, 2006 IEEE International Conference on Evolutionary Computation.

Learning from the Past: Regularization by Validation

M. Wahib, M. Munetomo, En-zhan Zhang, 2022, 2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS).

How to Apply Evolutionary Computation

Masaharu Munetomo, Hiroshi Someya, M. Munetomo, 2012 .

Solving Large Instances of Capacitated Vehicle Routing Problem over Cell BE

Asim Munawar, Mohamed Wahib, Masaharu Munetomo, 2008, 2008 10th IEEE International Conference on High Performance Computing and Communications.

Multiobjective Level-Wise Scientific Workflow Optimization in IaaS Public Cloud Environment

Masaharu Munetomo, Courtney Powell, Martin Schlueter, 2017, Sci. Program..

A Level-Wise Load Balanced Scientific Workflow Execution Optimization Using NSGA-II

Masaharu Munetomo, Courtney Powell, Martin Schlueter, 2017, 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID).

Load Balancing Routing with Genetic Algorithm Based on Link Load Metric

Masaharu Munetomo, Kiyoshi Akama, Yoshiharu Sato, 2002 .

Network Routing with the Use of Evolutionary Methods

Masaharu Munetomo, M. Munetomo, 2000, Computational Intelligence in Telecommunications Networks.

Identifying Linkage Groups by Nonlinearity/Non-monotonicity Detection

Masaharu Munetomo, M. Munetomo, 1999 .

Population Sizing of Dependency Detection by Fitness Difference Classification

Masaharu Munetomo, Kiyoshi Akama, Miwako Tsuji, 2005, FOGA.

A Parallel Genetic Algorithm Based on Linkage Identification

Masaharu Munetomo, Kiyoshi Akama, Naoya Murao, 2003, GECCO.

Linkage identification based on epistasis measures to realize efficient genetic algorithms

Masaharu Munetomo, M. Munetomo, 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

Surrogate Ensemble-Assisted Hyper-Heuristic Algorithm for Expensive Optimization Problems

M. Munetomo, Rui Zhong, Chao Zhang, 2023, International Journal of Computational Intelligence Systems.