Paper Titles
Prediction of Spring Back of the Two-Axle Rotary Shaping Based on Neural Network
p.1044
Research on Man-Machine Cooperation Manipulator and Information Integrated Technology in Advanced Manufacturing
p.1048
An Exploratory Study of Logistics Service Quality Model
p.1052
A Study on Multi-Colony Diploid Immune Algorithm and Its Application in Manufacture
p.1056
A Study on the Aviation Manufacture Cell Scheduling Based on Adaptive Ant Colony Algorithm
p.1060
Framework of Virtual Private Supply Chain Management
p.1064
Study on Approach to Fuzzy Product Configuration Based on Vague Customer Requirements
p.1068
Reconfigurable Manufacturing Execution Systems Based on Model-Driven Architecture
p.1072
Research on the Problem of MC Assembly Line Balancing Based on Genetic Algorithm
p.1076

A Study on the Aviation Manufacture Cell Scheduling Based on Adaptive Ant Colony Algorithm

Article Preview

Abstract:

Aviation manufacture cell scheduling is generally multi-constraint and multi-objective flexible job-shop scheduling, and is more complicated than classical job-shop because of flexible processing route, multi-restriction, multi-objective, dynamic disturb and complex model. The model of aviation manufacture cell scheduling is set up, and accordingly adaptive ant colony algorithm is brought forward. The adaptive mechanism and the genetic principle are introduced into the algorithm to accelerate convergence and avoid stagnation. Finally, the aviation manufacture cell scheduling of Xi’an Aero-Engine (Group) Ltd. is well solved by the proposed methods.

You might also be interested in these eBooks
Advances in Materials Manufacturing Science and Technology II View Preview

Info:

Periodical:

Materials Science Forum (Volumes 532-533)

Pages:

1060-1063

DOI:

https://doi.org/10.4028/www.scientific.net/MSF.532-533.1060

Citation:

Cite this paper

Online since:

December 2006

Authors:

Jian Jun Yu, Shu Dong Sun, Shu Bin Si, Hong An Yang, Xiu Li Wu

Keywords:

Adaptive, Ant Colony Algorithm (ACA), Aviation Manufacture Cell, Genetic Operator, Multi-Objective, Scheduling

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

© 2006 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

References

[1] A. Colorni, M. Dorigo and V. Maniezzo: Distributed optimization by ant colonies. The First of European Conference on Artificial Life, Paris, France: Elsevier Publishing, (1991), pp.134-142.

Google Scholar

[2] J.J. Yu, S.D. Sun and J.H. Hao: Research on Multi-objective Flexible Job-shop Scheduling Based on Immune Algorithm. Computer Integration Manufacturing System, (2006).

Google Scholar