Ant Colony Optimization with Genetic Operation and Its Application to Traveling Salesman Problem
スポンサーリンク
概要
- 論文の詳細を見る
- 2009-05-01
著者
-
WANG Rong-Long
Faculty of Engineering, Fukui University
-
Wang Rong-long
Faculty Of Engineering Toyama University
-
ZHOU Xiao-Fan
Faculty of Engineering, University of Fukui
-
OKAZAKI Kozo
Faculty of Engineering, University of Fukui
-
Okazaki Kozo
Faculty Of Engineering University Of Fukui
-
Zhou Xiao-fan
Faculty Of Engineering University Of Fukui
-
Wang Rong-long
Faculty Of Engineering Fukui University
関連論文
- Ant Colony Optimization with Genetic Operation and Its Application to Traveling Salesman Problem
- A Local Search Based Learning Method for Multiple-Valued Logic Networks(Neural Networks and Bioengineering)
- A Multi-Layered Immune System for Graph Planarization Problem
- An Artificial Immune System with Feedback Mechanisms for Effective Handling of Population Size
- A Near-Optimum Parallel Algorithm for a Graph Layout Problem(Neural Networks and Bioengineering)
- Ant Colony Optimization with Genetic Operation and Its Application to Traveling Salesman Problem
- A Genetic Algorithm with Conditional Crossover and Mutation Operators and Its Application to Combinatorial Optimization Problems(Neural Networks and Bioengineering)
- Solving Maximum Cut Problem Using Improved Hop field Neural Network
- A New Updating Procedure in the Hopfield-Type Network and Its Application to N-Queens Problem
- A Near-Optimum Parallel Algorithm for Bipartite Subgraph Problem Using the Hopfield Neural Network Learning
- Solving the Graph Planarization Problem Using an Improved Genetic Algorithm(Numerical Analysis and Optimization)
- A Hill-Shift Learning Algorithm of Hopfield Network for Bipartite Subgraph Problem(Neural Networks and Bioengineering)
- Solving the Bipartite Subgraph Problem Using Genetic Algorithm with Conditional Genetic Operators
- Solving Facility Layout Problem Using an Improved Genetic Algorithm(Numerical Analysis and Optimization)
- Solving the m-Way Graph Partitioning Problem Using a Genetic Algorithm