An Ant Colony Algorithm Method for Multi-Objective Production System

Chun Hsiung Lan; Kuo Torng Lan; Tzu Ying Hung

doi:10.4028/www.scientific.net/AMM.182-183.2071

Paper Titles

Airspace Congestion Prediction Based on Evidence Theory
p.2050

Improved Ant Colony Optimization and Application on TSP
p.2055

Trusted Bootstrap of Para-Virtualized Domain
p.2059

A New Method for MIMO-OFDM Channel Estimation Based on Discrete Wavelet Transform
p.2066

An Ant Colony Algorithm Method for Multi-Objective Production System
p.2071

Two-Factor Authenticated Key Exchange Protocol in the Three-Party Setting
p.2075

Auto White Balance Algorithm in Digital Camera
p.2080

Corrective Maintenance Based Vulnerability Repair Procedure to Improve Web Application Security
p.2085

Study on Utility Maximization Effectiveness in Packet Network Coding
p.2091

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 182-183An Ant Colony Algorithm Method for Multi-Objective...

An Ant Colony Algorithm Method for Multi-Objective Production System

Abstract:

This paper proposed a mathematical model called Multi-objective Production System Design (MOPSD) model solved by Ant Colony Optimization (ACO). The MOPSD model placed a production system under the constrained factory space to achieve the minimal total material transportation flow cost. This paper discussed 2-phase pheromone layout procedure that we proposed how to transform the best design information into and the relationship and tracing technology. After modeling experiment we proved it can be put the best design information into 2-phase pheromone layout procedure and achieved the minimal total material transportation flow cost by simply tracing technology.

You might also be interested in these eBooks

Applied Mechanics and Mechatronics Automation

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 182-183)

Pages:

2071-2074

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.182-183.2071

Citation:

Cite this paper

Online since:

June 2012

Authors:

Chun Hsiung Lan, Kuo Torng Lan, Tzu Ying Hung

Keywords:

Ant Colony Optimization (ACO), Multi-Objective Production System, Pheromone

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] M. Dorigo and T. Stutzle, Ant Coloby Optimization, the MIT Press, Cambridge, Massachusetts, (2004).

Google Scholar

[2] Chung-jen Kang and Chun-hsiung Lan, Multi-Objective Production System Design under Constrained Space, Unpublished doctoral dissertation, (2006).

Google Scholar

[3] D. Gong, G. Ymazaki, M. Gen, and W. Xu, A genetic algorithm method for one-dimensional machine location problems, Int. J. Production Economics, vol. 60-61, 1999, pp.337-342.

DOI: 10.1016/s0925-5273(98)00163-7

Google Scholar

[4] A. Misevicius, Genetic algorithm hybridized with ruin and recreate procedure: application to the quadratic assignment problem, Knowledge-Based Syst., vol. 16, no. 5-6, 2003, pp.261-268.

DOI: 10.1016/s0950-7051(03)00027-3

Google Scholar

[5] Kuo-Torng Lan, Analysis and Application of Competing Evolutionary Algorithms to Nonlinear Dynamic Systems, Unpublished doctoral dissertation, (2000).

Google Scholar

[6] D. Gong, G. Ymazaki, M. Gen, and W. Xu, A genetic algorithm method for one-dimensional machine location problems, Int. J. Production Economics, vol. 60-61, 1999, pp.337-342.

DOI: 10.1016/s0925-5273(98)00163-7

Google Scholar

[7] A. Misevicius, Genetic algorithm hybridized with ruin and recreate procedure: application to the quadratic assignment problem, Knowledge-Based Syst., vol. 16, no. 5-6, 2003, pp.261-268.

DOI: 10.1016/s0950-7051(03)00027-3

Google Scholar