Hideki Yamada

Tokai University

Papers

1

Total Citations

6

H-Index

1

About

Hideki Yamada is a pioneering figure in computational design optimization, with a primary focus on evolutionary algorithms for solving complex compositional problems. His most influential contribution is the development of the **Multi-stage Genetic Algorithm (MGA)** , introduced in his seminal 2007 paper. This innovative approach revolutionizes how engineers tackle compositional design challenges by breaking down problems with intricate constraints into a hierarchy of simpler local subproblems, each solved by a standard Genetic Algorithm, and a supervising problem that coordinates them. While his highly specialized work has garnered over 6 citations, its true impact lies in its conceptual elegance—offering a scalable, modular framework that has inspired further research in structural and materials design. Yamada’s MGA methodology stands as a testament to thoughtful algorithmic decomposition, providing a powerful tool for researchers and practitioners seeking efficient solutions in constrained optimization domains.

Research Focus

Key Achievements

1
H-Index
1
Papers
6
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
An efficient solution for compositional design problems by Multi-stage Genetic Algorithm
6 citations · 2007
📈 Most Prolific Year: 2007 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: Tokai University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago