Tree structure genetic algorithm with a nourishment mechanism

1997 ◽  
pp. 482-491
Author(s):  
Zhangang Han ◽  
Ruqian Lu
Keyword(s):  
Genetic Algorithm ◽  
Tree Structure

Piecewise linear classifiers using binary tree structure and genetic algorithm

1996 ◽  
Vol 29 (11) ◽  
pp. 1905-1917 ◽  
Author(s):  
Bing-Bing Chai ◽  
Tong Huang ◽  
Xinhua Zhuang ◽  
Yunxin Zhao ◽  
Jack Sklansky
Keyword(s):  
Genetic Algorithm ◽  
Binary Tree ◽  
Piecewise Linear ◽  
Tree Structure ◽  
Linear Classifiers ◽  
Binary Tree Structure

Form Innovation Method Based on Genetic Algorithm and Product Semantics

2013 ◽  
Vol 422 ◽  
pp. 336-342 ◽  
Author(s):  
Ying Li ◽  
Yan Pu Yang ◽  
Deng Kai Chen ◽  
Sui Huai Yu
Keyword(s):  
Genetic Algorithm ◽  
Evolutionary Computation ◽  
Visual Basic ◽  
Tree Structure ◽  
Product Form ◽  
Design System ◽  
Innovative Design ◽  
Mutation Operators ◽  
Product Semantics ◽  
Crossover And Mutation

From the perspective of combination principles, product form is divided into several modules for extracting profile curves; applying Genetic Algorithm (GA), product form chromosomes are coded in tree structure, through crossover and mutation operators to generate new programs; the method of product semantics is introduced into the process of evolutionary computation to enhance the interactivity of evolutionary computation by fuzzification, in which designer can decide the orientation from the selected products and guarantee the results can reflect the designer's innovative ideas. With Visual Basic and Rhinoceros platform a product form innovative design system is developed.

GA-BASED ALTERNATIVE APPROACHES FOR THE DEGREE-CONSTRAINED SPANNING TREE PROBLEM

2009 ◽  
Vol 23 (01) ◽  
pp. 129-144
Author(s):  
GENGUI ZHOU ◽  
ZHENYU CAO ◽  
ZHIQING MENG ◽  
JIAN CAO
Keyword(s):  
Genetic Algorithm ◽  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
Practical Importance ◽  
Numerical Results ◽  
Tree Structure ◽  
Np Hard ◽  
Optimal Solutions ◽  
Alternative Approaches ◽  
Prüfer Number

The degree-constrained minimum spanning tree (dc-MST) problem is of high practical importance. Up to now there are few effective algorithms to solve this problem because of its NP-hard complexity. More recently, a genetic algorithm (GA) approach for this problem was tried by using Prüfer number to encode a spanning tree. The Prüfer number is a skillful encoding for tree but not efficient enough to deal with the dc-MST problem. In this paper, a new tree-based encoding is developed directly based on the tree structure. We denote it as tree-based permutation encoding and apply it to the dc-MST problem by using the GA approach. Compared with the numerical results and CPU runtimes between two encodings, the new tree-based permutation is effective to deal with the dc-MST problem and even more efficient than the Prüfer number to evolve to the optimal or near-optimal solutions.

Distribution network planning based on tree structure encoding partheno-genetic algorithm

2008 ◽  
Author(s):  
Wenjun Zhang ◽  
Haozhong Cheng ◽  
Saiyi Wang ◽  
Yinong Li ◽  
Jianmin Wang
Keyword(s):  
Genetic Algorithm ◽  
Distribution Network ◽  
Network Planning ◽  
Tree Structure ◽  
Distribution Network Planning

Man-Computer Derivations of Tree Structure from Multivariate Data

1968 ◽  
Author(s):  
Gerald H. Shure ◽  
Laurence I. Press ◽  
Miles S. Rogers
Keyword(s):  
Multivariate Data ◽  
Tree Structure

Building a tree structure

1976 ◽  
Author(s):  
Patricia Marks Greenfield ◽  
Leslie Schneider
Keyword(s):  
Tree Structure
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