World's Best Scientists 2026 revealed!
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Computer Science
Japan
2026

D-Index & Metrics

Computer Science

D-Index
77
Citations
41983
World Ranking
1233
National Ranking
6

Research.com Recognitions

  • 2026 - Research.com Computer Science in Japan Leader Award
  • 2025 - Research.com Computer Science in Japan Leader Award
  • 2023 - Research.com Computer Science in Japan Leader Award
  • 2022 - Research.com Computer Science in Japan Leader Award
  • 2016 - IEEE Transactions on Semiconductor Manufacturing Best Paper Award

Overview

Mitsuo Gen is affiliated with the Tokyo University of Science in Japan. Their research work primarily spans the fields of Engineering, Computer Science, and Business, Management and Accounting. The main subfields of study include Industrial and Manufacturing Engineering, Artificial Intelligence, Strategy and Management, Computational Theory and Mathematics, and Management Information Systems.

The scientist's research focuses on topics such as Scheduling and Optimization Algorithms, Advanced Manufacturing and Logistics Optimization, Metaheuristic Optimization Algorithms Research, Advanced Multi-Objective Optimization Algorithms, Assembly Line Balancing Optimization, Sustainable Supply Chain Management, and Supply Chain and Inventory Management.

Frequent co-authors collaborating with Mitsuo Gen include Wenqiang Zhang, Guohui Zhang, Jianquan Guo, YoungSu Yun, and Weidong Yang.

Common publication venues where Mitsuo Gen's work appears are:

  • Computers & Industrial Engineering
  • International Journal of Management Science and Engineering Management
  • Mathematical Biosciences & Engineering
  • International Journal of Internet Manufacturing and Services
  • Frontiers in Industrial Engineering

Notable recent papers published by Mitsuo Gen include:

  • Research on green closed-loop supply chain with the consideration of double subsidy in e-commerce environment, 2020, Computers & Industrial Engineering
  • A multiobjective memetic algorithm with particle swarm optimization and Q-learning-based local search for energy-efficient distributed heterogeneous hybrid flow-shop scheduling problem, 2023, Expert Systems with Applications
  • Multi-objective multi-mode resource-constrained project scheduling with fuzzy activity durations in prefabricated building construction, 2021, Computers & Industrial Engineering
  • Sustainable Closed-Loop Supply Chain Design Problem: A Hybrid Genetic Algorithm Approach, 2020, Mathematics
  • Multidirection Update-Based Multiobjective Particle Swarm Optimization for Mixed No-Idle Flow-Shop Scheduling Problem, 2021, Complex System Modeling and Simulation

Best Publications

  • Genetic algorithms and engineering optimization

    Mitsuo Gen;Runwei Cheng

  • Genetic Algorithms

    Mitsuo Gen;Runwei Cheng

  • Genetic algorithms and engineering design

    Unknown

  • A tutorial survey of job-shop scheduling problems using genetic algorithms—I: representation

    Runwei Cheng;Mitsuo Gen;Yasuhiro Tsujimura

  • A genetic algorithm approach for multi-objective optimization of supply chain networks

    Fulya Altiparmak;Mitsuo Gen;Lin Lin;Turan Paksoy

  • Network Models and Optimization: Multiobjective Genetic Algorithm Approach

    Mitsuo Gen;Runwei Cheng;Lin Lin

  • A hybrid genetic and variable neighborhood descent algorithm for flexible job shop scheduling problems

    Jie Gao;Linyan Sun;Mitsuo Gen

  • A tutorial survey of job-shop scheduling problems using genetic algorithms, part II: hybrid genetic search strategies

    Runwei Cheng;Mitsuo Gen;Yasuhiro Tsujimura

  • Study on multi-stage logistic chain network: a spanning tree-based genetic algorithm approach

    Admi Syarif;YoungSu Yun;Mitsuo Gen

  • A genetic algorithm for two-stage transportation problem using priority-based encoding

    Mitsuo Gen;Fulya Altiparmak;Lin Lin

  • Intelligent Engineering Systems Through Artificial Neural Networks

    Cihan H. Dagli;K. Mark Bryden;Steven M. Corns;Mitsuo Gen

  • A genetic algorithm based approach to vehicle routing problem with simultaneous pick-up and deliveries

    A. Serdar Tasan;Mitsuo Gen

  • A steady-state genetic algorithm for multi-product supply chain network design

    Fulya Altiparmak;Mitsuo Gen;Lin Lin;Ismail Karaoglan

  • A hybrid of genetic algorithm and bottleneck shifting for multiobjective flexible job shop scheduling problems

    Jie Gao;Mitsuo Gen;Linyan Sun;Xiaohui Zhao

  • Genetic algorithm approach on multi-criteria minimum spanning tree problem

    Gengui Zhou;Mitsuo Gen

  • Genetic algorithm for non-linear mixed integer programming problems and its applications

    Takao Yokota;Mitsuo Gen;Yin-Xiu Li

  • Network model and optimization of reverse logistics by hybrid genetic algorithm

    Jeong-Eun Lee;Mitsuo Gen;Kyong-Gu Rhee

  • Hybrid genetic algorithm for multi-time period production/distribution planning

    Mitsuo Gen;Admi Syarif

  • The balanced allocation of customers to multiple distribution centers in the supply chain network: a genetic algorithm approach

    Gengui Zhou;Hokey Min;Mitsuo Gen

  • Soft computing approach for reliability optimization: State-of-the-art survey

    Mitsuo Gen;YoungSu Yun

  • Genetic algorithms for solving shortest path problems

    M. Gen;Runwei Cheng;Dingwei Wang

  • Foundations of Genetic Algorithms

    Mitsuo Gen;Mitsuo Gen;Runwei Cheng

Frequent Co-Authors

Chen-Fu Chien
Chen-Fu Chien National Tsing Hua University
Hisao Ishibuchi
Hisao Ishibuchi Southern University of Science and Technology
Hark Hwang
Hark Hwang Korea Advanced Institute of Science and Technology
Baoding Liu
Baoding Liu Tsinghua University
Kap Hwan Kim
Kap Hwan Kim Pusan National University
Sang M. Lee
Sang M. Lee University of Nebraska–Lincoln
Reza Tavakkoli-Moghaddam
Reza Tavakkoli-Moghaddam University of Tehran
Jiuping Xu
Jiuping Xu Sichuan University
Gwo-Hshiung Tzeng
Gwo-Hshiung Tzeng National Taipei University
Kagan Tumer
Kagan Tumer Oregon State University

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