A new solution to optimization-satisfaction problems by a penalty method. - Kiyotaka Shimizu; Eitaro Aiyoshi (Autom., 1982)

Double penalty method for bilevel optimization problems. - Yo Ishizuka; Eitaro Aiyoshi (Ann. Oper. Res., 1992)

The hierarchical and social decision making procedure for bi-objective optimization problems by using the simple majority decision rule. - Keiko Nagase; Eitaro Aiyoshi (J. Glob. Optim., 1996)

Neural networks realization of searching models for Nash equilibrium points and their application to associative memories. - Ryota Horie; Eitaro Aiyoshi (SMC, 1998)

A distributed model of the saccade system: simulations of temporally perturbed saccades using position and velocity feedback. - Kuniharu Arai; Sanjoy Das; Edward L. Keller; Eitaro Aiyoshi (Neural Networks, 1999)

An application of the continuous time replicator dynamic to economics. - Eitaro Aiyoshi; Ryota Horie; Atsushi Maki (Math. Comput. Simul., 2002)

Integrative two-state optimization for core design of BWR using genetic algorithms. - Yoko Kobayashi; Eitaro Aiyoshi (CCA, 2003)

Automatic core design using reinforcement learning. - Yoko Kobayashi; Eitaro Aiyoshi (ACC, 2004)

Optimization algorithm using multi-agents and reinforcement learning. - Yoko Kobayashi; Eitaro Aiyoshi (IEEE Congress on Evolutionary Computation, 2004)

Recurrent network expression and its property of replicator dynamics for optimization. - Kazuaki Masuda; Eitaro Aiyoshi (SMC (4), 2004)

Automatic Tuning for Model Predictive Control: Can Particle Swarm Optimization find a better parameter? - Fukiko Kawai; Hideyuki Ito; Chikashi Nakazawa; Tetsuro Matsui; Yoshikazu Fukuyama; Ryohei Suzuki; Eitaro Aiyoshi (ISIC, 2007)

Automatic Tuning of Model Predictive Control Using Particle Swarm Optimization. - Ryohei Suzuki; Fukiko Kawai; Hideyuki Ito; Chikashi Nakazawa; Yoshikazu Fukuyama; Eitaro Aiyoshi (SIS, 2007)

Global optimization using a synchronization of multiple search Points autonomously driven by a chaotic dynamic model. - Takashi Okamoto; Eitaro Aiyoshi (J. Glob. Optim., 2008)

A Nash equilibrium solution in an oligopoly market: The search for Nash equilibrium solutions with replicator equations derived from the gradient dynamics of a simplex algorithm. - Eitaro Aiyoshi; Atsushi Maki (Math. Comput. Simul., 2009)

A penalty approach to handle inequality constraints in particle swarm optimization. - Kazuaki Masuda; Kenzo Kurihara; Eitaro Aiyoshi (SMC, 2010)

A novel method for solving min-max problems by using a modified particle swarm optimization. - Kazuaki Masuda; Kenzo Kurihara; Eitaro Aiyoshi (SMC, 2011)

The robustness of a Nash equilibrium simulation model: Game-theoretic approach using variable metric projection method. - Eitaro Aiyoshi; Atsushi Maki; Takashi Okamoto (Math. Comput. Simul., 2011)

Gamification of the Optimization Problem and Multi-point Type Optimization Methods. - Takashi Okamoto; Eitaro Aiyoshi (SMC, 2013)

A New Framework with a Stability Theory for Multipoint-Type and Stochastic Meta-Heuristic Optimization Algorithms. - Yuji Koguma; Eitaro Aiyoshi (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2015)

A three-compartment non-linear model of myocardial cell conduction block during photosensitization. - Emiyu Ogawa; Eitaro Aiyoshi; Tsunenori Arai (Medical Biol. Eng. Comput., 2021)