| 2009 |
|---|
| 32 | EE | Tadahiko Murata,
Akinori Taki:
Many-Objective Optimization for Knapsack Problems Using Correlation-Based Weighted Sum Approach.
EMO 2009: 468-480 |
| 2007 |
|---|
| 31 | | Shigeru Obayashi,
Kalyanmoy Deb,
Carlo Poloni,
Tomoyuki Hiroyasu,
Tadahiko Murata:
Evolutionary Multi-Criterion Optimization, 4th International Conference, EMO 2007, Matsushima, Japan, March 5-8, 2007, Proceedings
Springer 2007 |
| 30 | EE | Tadahiko Murata,
Yusuke Aoki:
Developing control table for multiple agents using GA-Based Q-learning with neighboring crossover.
IEEE Congress on Evolutionary Computation 2007: 1462-1467 |
| 29 | EE | Daisuke Banjo,
Hiroyuki Tamura,
Tadahiko Murata:
Simulating a Transition Process to Generation-based Funding Scheme in Public Pension Planning.
SMC 2007: 1993-1998 |
| 28 | EE | Tadahiko Murata,
Hiroshi Arikawa,
Sen-ichi Morishita,
Taiyo Maeda:
A Design of Problem Solving Environments for Policy Making Assistance Using MAS-Based Social Simulation.
eScience 2007: 521-528 |
| 2006 |
|---|
| 27 | EE | Tadahiko Murata,
Ryota Itai:
Local Search in Two-Fold EMO Algorithm to Enhance Solution Similarity for Multi-objective Vehicle Routing Problems.
EMO 2006: 201-215 |
| 2005 |
|---|
| 26 | EE | Tadahiko Murata,
Masatoshi Yamaguchi:
Neighboring crossover to improve GA-based Q-learning method for multi-legged robot control.
GECCO 2005: 145-146 |
| 25 | EE | Tadahiko Murata,
Takashi Nakamura:
Genetic network programming with automatically defined groups for assigning proper roles to multiple agents.
GECCO 2005: 1705-1712 |
| 2004 |
|---|
| 24 | EE | Tadahiko Murata,
Takashi Nakamura:
Multi-agent Cooperation Using Genetic Network Programming with Automatically Defined Groups.
GECCO (2) 2004: 712-714 |
| 23 | | Tadahiko Murata,
Nobuaki Kakito:
Products' review page projection using the number of evaluating expressions.
ICWI 2004: 1061-1064 |
| 22 | | Tadahiko Murata,
Shoko Shirato:
History using browsing duration to assist browsing activity.
ICWI 2004: 1121-1124 |
| 21 | EE | Tadahiko Murata,
Hiroshi Matsumoto:
Use of Successful Policies to Relearn for Induced States of Failure in Reinforcement Learning.
KES 2004: 1114-1120 |
| 20 | EE | Tadahiko Murata,
Kenji Takada:
Performance Evaluation of a Distributed Genetic Algorithm with Cellular Structures on Function Optimization Problems.
KES 2004: 1128-1135 |
| 19 | EE | Tadahiko Murata,
Yu Mizoguchi:
Generation and recall method for long-term memory data to suppress interference in RAN.
SMC (6) 2004: 5697-5701 |
| 2003 |
|---|
| 18 | EE | Tadahiko Murata,
Hiroyuki Nozawa,
Hisao Ishibuchi,
Mitsuo Gen:
Modification of Local Search Directions for Non-dominated Solutions in CellularMultiobjective Genetic Algorithms forPattern Classification Problems.
EMO 2003: 593-607 |
| 17 | EE | Tadahiko Murata,
Shiori Kaige,
Hisao Ishibuchi:
Generalization of Dominance Relation-Based Replacement Rules for Memetic EMO Algorithms.
GECCO 2003: 1234-1245 |
| 16 | | Hisao Ishibuchi,
Tadashi Yoshida,
Tadahiko Murata:
Balance between genetic search and local search in memetic algorithms for multiobjective permutation flowshop scheduling.
IEEE Trans. Evolutionary Computation 7(2): 204-223 (2003) |
| 2002 |
|---|
| 15 | | Hisao Ishibuchi,
Tadashi Yoshida,
Tadahiko Murata:
Balance Between Genetic Search And Local Search In Hybrid Evolutionary Multi-criterion Optimization Algorithms.
GECCO 2002: 1301-1308 |
| 2001 |
|---|
| 14 | EE | Hisao Ishibuchi,
Tomoharu Nakashima,
Tadahiko Murata:
Multiobjective Optimization in Linguistic Rule Extraction from Numerical Data.
EMO 2001: 588-602 |
| 13 | EE | Tadahiko Murata,
Hisao Ishibuchi,
Mitsuo Gen:
Specification of Genetic Search Directions in Cellular Multi-objective Genetic Algorithms.
EMO 2001: 82-95 |
| 12 | | Hisao Ishibuchi,
Tomoharu Nakashima,
Tadahiko Murata:
Three-objective genetics-based machine learning for linguistic rule extraction.
Inf. Sci. 136(1-4): 109-133 (2001) |
| 2000 |
|---|
| 11 | | Tadahiko Murata,
Hisao Ishibuchi,
Mitsuo Gen:
Cellular Genetic Local Search for Multi-Objective Optimization.
GECCO 2000: 307-314 |
| 1999 |
|---|
| 10 | | Hisao Ishibuchi,
Tomoharu Nakashima,
Tadahiko Murata:
Performance evaluation of fuzzy classifier systems for multidimensional pattern classification problems.
IEEE Transactions on Systems, Man, and Cybernetics, Part B 29(5): 601-618 (1999) |
| 9 | EE | Hisao Ishibuchi,
Tadahiko Murata,
Tomoharu Nakashima:
Linguistic Rule Extraction from Numerical Data for High-dimensional Classification Problems.
JACIII 3(5): 386-393 (1999) |
| 1998 |
|---|
| 8 | | Tadahiko Murata,
Hisao Ishibuchi,
Tomoharu Nakashima,
Mitsuo Gen:
Fuzzy Partition and Input Selection by Genetic Algorithms for Designing Fuzzy Rule-Based Classification Systems.
Evolutionary Programming 1998: 407-416 |
| 7 | EE | Tadahiko Murata,
Hisao Ishibuchi,
Mitsuo Gen:
Neighborhood structures for genetic local search algorithms.
KES (2) 1998: 259-263 |
| 1997 |
|---|
| 6 | | Hisao Ishibuchi,
Tadahiko Murata,
Shigemitsu Tomioka:
Effectiveness of Genetic Local Search Algorithms.
ICGA 1997: 505-512 |
| 1996 |
|---|
| 5 | | Hisao Ishibuchi,
Tadahiko Murata:
Multi-Objective Genetic Local Search Algorithm.
International Conference on Evolutionary Computation 1996: 119-124 |
| 4 | | Tadahiko Murata,
Hisao Ishibuchi:
Positive and Negative Combination Effects of Crossover and Mutation Operators in Sequencing Problems.
International Conference on Evolutionary Computation 1996: 170-175 |
| 3 | | Hisao Ishibuchi,
Tomoharu Nakashima,
Tadahiko Murata:
Genetic-Algorithm-Based Approaches to the Design of Fuzzy Systems for Multi-Dimensional Pattern Classification Problems.
International Conference on Evolutionary Computation 1996: 229-234 |
| 1995 |
|---|
| 2 | | Hisao Ishibuchi,
Tomoharu Nakashima,
Tadahiko Murata:
A Fuzzy Classifier System That Generates Linguistic Rules for Pattern Classification Problems.
IEEE/Nagoya-University World Wisepersons Workshop 1995: 35-54 |
| 1994 |
|---|
| 1 | | Tadahiko Murata,
Hisao Ishibuchi:
Performance Evaluation of Genetic Algorithms for Flowshop Scheduling Problems.
International Conference on Evolutionary Computation 1994: 812-817 |
