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International Conference on Information Technology and Management Engineering (ITME 2011)Available to Purchase
Editor
W. X. Wang
W. X. Wang
Royal Institute of Technology
, Sweden
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ISBN:
9780791859827
No. of Pages:
500
Publisher:
ASME Press
Publication date:
2011
eBook Chapter
28 Improved Method of GA's Initiation Population Based on Local-Effective-Information for Solving TSP Available to Purchase
By
Yuyu Meng
,
Yuyu Meng
School of Electronics & Information Engineering,
Lanzhou Jiaotong University
, Lanzhou 730070
China
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Liying Zheng
Liying Zheng
School of Electronics & Information Engineering,
Lanzhou Jiaotong University
, Lanzhou, 730070
, China
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Page Count:
3
-
Published:2011
Citation
Meng, Y, & Zheng, L. "Improved Method of GA's Initiation Population Based on Local-Effective-Information for Solving TSP." International Conference on Information Technology and Management Engineering (ITME 2011). Ed. Hu, WB, & Wang, WX. ASME Press, 2011.
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Genetic Algorithm (GA) is restricted by actual system computing ability. Because of the limited number of population and iteration, the choice of initiation Population is a vital of fact, which directly influents the result of algorithm and the efficiency. GA's Initiation Population is created by the path of well-proportioned choosing seed or stochastic choosing seed generally, but both of them have a vice of inefficient search. The paper, combining with interrelated theories in graph theory, brings forward two kinds of Optimization Algorithms of Initiation Population based on Minimize Spanning Tree Local-Effective-Information Theory towards the limitations of them, and we successes it to TSP by example analysis.
Abstract
Keywords
Introduction
Nomenclature
2 The construction algorithm based on minimal spanning tree
3 Example solutions
4 Conclusions
References
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