Application of Genetic Algorithm to Scheduling Problems in Manufacturing Processes. - Nobuo Sannomiya; Hitoshi Iima (International Conference on Evolutionary Computation, 1996)

An autonomous decentralized scheduling algorithm for a job shop process with a multi-function machine in parallel. - Hitoshi Iima; Ryoichi Kudo; Nobuo Sannomiya; Yasunori Kobayashi (ISADS, 1997)

Autonomous Decentralized Scheduling Algorithm for a Job-Shop Scheduling Problem with Complicated Constraints. - Hitoshi Iima; Tetsuya Hara; Norihisa Ichimi; Nobuo Sannomiya (ISADS, 1999)

An autonomous decentralized scheduling algorithm for a scheduling problem in a metal mould assembly process. - Hitoshi Iima; Ryoichi Kudo; Nobuo Sannomiya; Yasunori Kobayashi (J. Intell. Manuf., 1999)

Module type genetic algorithm for modified scheduling problems with worker allocation. - Hitoshi Iima; Nobuo Sannomiya (ACC, 2001)

A new design of genetic algorithm for bin packing. - Hitoshi Iima; T. Yakawa (IEEE Congress on Evolutionary Computation, 2003)

Proposition of Selection Operation in a Genetic Algorithm for a Job Shop Rescheduling Problem. - Hitoshi Iima (EMO, 2005)

Parallel genetic algorithm for a multiobjective rescheduling problem. - Hitoshi Iima (Artificial Intelligence and Soft Computing, 2006)

A Learning Method for Synthesizing Spiking Neural Oscillators. - Yasuaki Kuroe; Hitoshi Iima (IJCNN, 2006)

Swarm reinforcement learning algorithms based on particle swarm optimization. - Hitoshi Iima; Yasuaki Kuroe (SMC, 2008)

Swarm Reinforcement Learning Algorithm Based on Particle Swarm Optimization Whose Personal Bests Have Lifespans. - Hitoshi Iima; Yasuaki Kuroe (ICONIP (2), 2009)

A method for Development of collaborative learning by using a neural network and a genetic algorithm. - Kazuhiro Shin-ike; Hitoshi Iima (ISADS, 2009)

Swarm Reinforcement Learning Method Based on an Actor-Critic Method. - Hitoshi Iima; Yasuaki Kuroe (SEAL, 2010)

Swarm reinforcement learning method based on ant colony optimization. - Hitoshi Iima; Yasuaki Kuroe; Shoko Matsuda (SMC, 2010)

A Method for Determining Classroom Seating Arrangements by Using Bioinformatics. - Kazuhiro Shin-ike; Hitoshi Iima (Edutainment, 2011)

Models of Hopfield-Type Clifford Neural Networks and Their Energy Functions - Hyperbolic and Dual Valued Networks -. - Yasuaki Kuroe; Shinpei Tanigawa; Hitoshi Iima (ICONIP (1), 2011)

Swarm reinforcement learning methods for problems with continuous state-action space. - Hitoshi Iima; Yasuaki Kuroe; Kazuo Emoto (SMC, 2011)

A Method for Determining Classroom Seating Arrangements by Using a Genetic Algorithm. - Kazuhiro Shin-ike; Hitoshi Iima (ICCE, 2012)

Multi-objective reinforcement learning method for acquiring all pareto optimal policies simultaneously. - Yusuke Mukai; Yasuaki Kuroe; Hitoshi Iima (SMC, 2012)

Swarm Reinforcement Learning Method for a Multi-robot Formation Problem. - Hitoshi Iima; Yasuaki Kuroe (SMC, 2013)

Multi-objective reinforcement learning for acquiring all Pareto optimal policies simultaneously - Method of determining scalarization weights. - Hitoshi Iima; Yasuaki Kuroe (SMC, 2014)

Swarm reinforcement learning methods improving certainty of learning for a multi-robot formation problem. - Hitoshi Iima; Yasuaki Kuroe (CEC, 2015)

Genetic Algorithms for Student Grouping Problems. - Hitoshi Iima; Kazuhiro Shin-ike (SMC, 2015)

A model of Hopfield-type octonion neural networks and existing conditions of energy functions. - Yasuaki Kuroe; Hitoshi Iima (IJCNN, 2016)

A Smart Framework towards Providing Benefits for One and All. - Teruhisa Hochin; Hiroki Nomiya; Hitoshi Iima; Morshed U. Chowdhury (ACIT/CSII/BCD, 2017)

Improving generalization ability in a puzzle game using reinforcement learning. - Hiroya Oonishi; Hitoshi Iima (CIG, 2017)

Nonlinear Optimization Method Based on Stochastic Gradient Descent for Fast Convergence. - Takahiro Watanabe; Hitoshi Iima (SMC, 2018)

Deep Learning for Designing an AI Player of the Puzzle Game Geometry Friends. - Hitoshi Iima; Hiroya Oonishi (CSII, 2019)

Differential Evolution Using Linkage Identification. - Hitoshi Iima; Keijiro Yokoyama (ICTAI, 2019)

Real-Coded Genetic Algorithm Realizing Fast Convergence by Reducing Its Population Size. - Kazuki Nishisaka; Hitoshi Iima (ICTAI, 2019)

Learning Method of Recurrent Spiking Neural Networks to Realize Various Firing Patterns using Particle Swarm Optimization. - Yasuaki Kuroe; Hitoshi Iima; Yutaka Maeda (IJCCI, 2019)

Design of an Artificial Game Entertainer by Reinforcement Learning. - Takanobu Yaguchi; Hitoshi Iima (CoG, 2020)

Four Models of Hopfield-Type Octonion Neural Networks and Their Existing Conditions of Energy Functions. - Yasuaki Kuroe; Hitoshi Iima; Yutaka Maeda (IJCNN, 2020)

Hyperheuristic Method Based on Deep Reinforcement Learning. - Hitoshi Iima; Yoshiyuki Nakamura (IIAI-AAI, 2022)

Genetic Algorithm with Machine Learning to Estimate the Optimal Objective Function Values of Subproblems. - Hitoshi Iima; Yohei Hazama (ISMSI, 2022)

Drone Scheduling for Parcel Delivery with a Given Truck Route and Setup Times. - Riki Kataoka; Yoshiyuki Karuno; Hitoshi Iima (SCIS/ISIS, 2022)

Accelerated Text Data Augmentation Using a Paraphrase Generation Model with Round-Trip Translation as a Supervisor. - Shintaro Tanaka; Hitoshi Iima (ICMLA, 2023)

CT to MRI Image Translation Using CycleGAN: A Deep Learning Approach for Cross-Modality Medical Imaging. - Anamika Jha; Hitoshi Iima (ICAART (3), 2024)

Foreign Exchange Rate Forecast by a Large Language Model Integrated with Trend Description. - Kexin Peng; Hitoshi Iima (ISCMI, 2024)

Integer Programming Approaches to an Issue of Scheduling for a Truck-Drone Last-Mile Delivery System with Parcel Pickup Service. - Kotaro Yamada; Yoshiyuki Karuno; Hitoshi Iima (SCIS/ISIS, 2024)

Classes of Dilemma Problems and Their Multi-Agent Reinforcement Learning Method. - Yasuaki Kuroe; Hitoshi Iima (IEEE Access, 2024)

Genetic Algorithms for a Scheduling Problem of Parcel Delivery and Pickup by Drones. - Yohei Hazama; Hitoshi Iima; Yoshiyuki Karuno (IEEE Access, 2025)