Application of Intelligence Fusion Algorithm in Path Optimization Problem

Shi Gang Wang; Yu Juan Wang; Guan Xiong Wu; Yi Li Fu

doi:10.4028/www.scientific.net/AMM.151.632

Paper Titles

A Global Stereo Matching Algorithm Based on Adaptive Support-Weight and Graph Cut
p.612

Research on Limitations for Stabilizability of Networked Controlled Systems
p.617

Fuzzy Control of Hydraulic Dynamometer Water Pressure Based on Visual C++
p.622

Chilled Water Temperature Control of HVAC System Using GPC Based Controller
p.626

Application of Intelligence Fusion Algorithm in Path Optimization Problem
p.632

Knowledge Structure of TRIZ Case Based on Situational Analogy
p.637

Wireless Communication System Development of Mobile Robot Based on Embedded Technology
p.641

Design of the Comprehensive Experimental Platform for Testing Technology Based on Virtual Instrument
p.646

A Novel Edge Detection Algorithm for Medical Image
p.653

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 151Application of Intelligence Fusion Algorithm in...

Application of Intelligence Fusion Algorithm in Path Optimization Problem

Abstract:

In CAD/CAM integration system, the problem of the path optimization to be thorough researched. Through numerical describe of information elements, by using graph theory of traveling salesman problem，set up the mathematical model of path optimization problem. Based on ant colony algorithm and lin-kernighan (LK) algorithm, an intelligence fusion algorithm is put forward. With group of holes processing as an example, the group of holes drilling tool path of optimized, and realize the CAD/CAM many features of optimization, which greatly improve the processing precision and efficiency.

You might also be interested in these eBooks

New Trends in Mechatronics and Materials Engineering

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volume 151)

Pages:

632-636

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.151.632

Citation:

Cite this paper

Online since:

January 2012

Authors:

Shi Gang Wang, Yu Juan Wang, Guan Xiong Wu, Yi Li Fu

Keywords:

Ant Colony Optimization (ACO), Group of Holes Processing, LK Algorithm, Path Optimization, Traveling Salesman Problem (TSP)

Export:

RIS, BibTeX

Price:

Permissions:

Request Permissions

References

[1] Huang Yan: CAD/CAM development trends. Technology and Innovation Management, Vol. 29, No. 1 (2008), pp.77-80.

Google Scholar

[2] Tian Meili: Optimization of tool path for hole manufacturing in CAD/CAM system. Manufacturing Technology & Machine Tool, No. 10 (2002), pp.15-16.

Google Scholar

[3] Grefenstette J J: Genetic algorithms for the traveling salesman problem. Proc of ICGA, No. 2 (1985), pp.160-168.

Google Scholar

[4] S. Lin, B. W. Kernighan: An effective heuristic algorithm for the traveling salesman problem. Operations Researeh, Vol. 21 (1973), pp.498-516.

DOI: 10.1287/opre.21.2.498

Google Scholar

[5] Keld Helsgaun: An effective implementation of the Lin-Kernighan traveling salesman heuristic. European Journal of Operational Research, Vol. 126 (2000), pp.106-130.

DOI: 10.1016/s0377-2217(99)00284-2

Google Scholar

[6] Badr Fahmy A: A proof of convergence for ant algorithms. Information International Journal on Intelligent Cooperative Information Systems, Vol. 3, No. 1 (2003), pp.22-32.

Google Scholar

[7] Waiter J, Guqahr: A graph-based ant system and its convergence. Future Generation ComPuter Systems, Vol. 16, No. 8 (2000), pp.873-888.

DOI: 10.1016/s0167-739x(00)00044-3

Google Scholar

[8] Walter J, Guqahr: ACO algorithms with guaranteed convergence to the Optimal Soften. Information Proeessing Letters, Vol. 82, No. 3 (2002), pp.145-153.

DOI: 10.1016/s0020-0190(01)00258-7

Google Scholar