Can ant algorithms make automated guided vehicle system more intelligent? A viewpoint from manufacturing environment

Bo Xing; Wen Jing Gao; Kimberly Battle; Tshilidzi Marwala; Fulufhelo V. Nelwamondo

doi:10.1109/ICSMC.2010.5642291

Can ant algorithms make automated guided vehicle system more intelligent? A viewpoint from manufacturing environment

Bo Xing
, Wen Jing Gao
, Kimberly Battle
, Tshilidzi Marwala
, Fulufhelo V. Nelwamondo

Faculty of Engineering and the Built Environment

University of Johannesburg
Council for Scientific and Industrial Research

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

13 Citations (Scopus)

Abstract

In manufacturing environment, an automated guided vehicle (AGV) system is composed of a set of driver-less vehicles that transport goods and materials between distinct workstations and storage locations of shops. In soft computing area, ant algorithms are a series of population-based approaches inspired by various behaviors of real ant colonies. During the last two decades, ant algorithms have achieved a great success in solving many combinatorial optimization problems. In this article we make an attempt to study the feasibility of applying ant algorithms to different problems encountered in AGV system design and control. By making use of ant algorithms' strengths, we hope to provide the readers with alternative options for solving conventional AGV system design and control problems, as well as to point out some new directions for AGV system research.

Original language	English
Title of host publication	2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010
Pages	3226-3234
Number of pages	9
DOIs	https://doi.org/10.1109/ICSMC.2010.5642291
Publication status	Published - 2010
Event	2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010 - Istanbul, Turkey Duration: 10 Oct 2010 → 13 Oct 2010

Publication series

Name	Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ISSN (Print)	1062-922X

Conference

Conference	2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010
Country/Territory	Turkey
City	Istanbul
Period	10/10/10 → 13/10/10

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

Ant algorithms
Automated guided vehicle
Cooperative transportation
Dispatching
Guide path
Loading unit
Mobile ad hoc network
Routing
Traffic control

ASJC Scopus subject areas

Electrical and Electronic Engineering
Control and Systems Engineering
Human-Computer Interaction

Access to Document

10.1109/ICSMC.2010.5642291

Cite this

Xing, B., Gao, W. J., Battle, K., Marwala, T., & Nelwamondo, F. V. (2010). Can ant algorithms make automated guided vehicle system more intelligent? A viewpoint from manufacturing environment. In 2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010 (pp. 3226-3234). Article 5642291 (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics). https://doi.org/10.1109/ICSMC.2010.5642291

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title = "Can ant algorithms make automated guided vehicle system more intelligent? A viewpoint from manufacturing environment",

abstract = "In manufacturing environment, an automated guided vehicle (AGV) system is composed of a set of driver-less vehicles that transport goods and materials between distinct workstations and storage locations of shops. In soft computing area, ant algorithms are a series of population-based approaches inspired by various behaviors of real ant colonies. During the last two decades, ant algorithms have achieved a great success in solving many combinatorial optimization problems. In this article we make an attempt to study the feasibility of applying ant algorithms to different problems encountered in AGV system design and control. By making use of ant algorithms' strengths, we hope to provide the readers with alternative options for solving conventional AGV system design and control problems, as well as to point out some new directions for AGV system research.",

keywords = "Ant algorithms, Automated guided vehicle, Cooperative transportation, Dispatching, Guide path, Loading unit, Mobile ad hoc network, Routing, Traffic control",

author = "Bo Xing and Gao, \{Wen Jing\} and Kimberly Battle and Tshilidzi Marwala and Nelwamondo, \{Fulufhelo V.\}",

year = "2010",

doi = "10.1109/ICSMC.2010.5642291",

language = "English",

isbn = "9781424465880",

series = "Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics",

pages = "3226--3234",

booktitle = "2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010",

note = "2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010 ; Conference date: 10-10-2010 Through 13-10-2010",

}

Xing, B, Gao, WJ, Battle, K, Marwala, T & Nelwamondo, FV 2010, Can ant algorithms make automated guided vehicle system more intelligent? A viewpoint from manufacturing environment. in 2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010., 5642291, Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, pp. 3226-3234, 2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010, Istanbul, Turkey, 10/10/10. https://doi.org/10.1109/ICSMC.2010.5642291

Can ant algorithms make automated guided vehicle system more intelligent? A viewpoint from manufacturing environment. / Xing, Bo; Gao, Wen Jing; Battle, Kimberly et al.
2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010. 2010. p. 3226-3234 5642291 (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - In manufacturing environment, an automated guided vehicle (AGV) system is composed of a set of driver-less vehicles that transport goods and materials between distinct workstations and storage locations of shops. In soft computing area, ant algorithms are a series of population-based approaches inspired by various behaviors of real ant colonies. During the last two decades, ant algorithms have achieved a great success in solving many combinatorial optimization problems. In this article we make an attempt to study the feasibility of applying ant algorithms to different problems encountered in AGV system design and control. By making use of ant algorithms' strengths, we hope to provide the readers with alternative options for solving conventional AGV system design and control problems, as well as to point out some new directions for AGV system research.

KW - Ant algorithms

KW - Automated guided vehicle

KW - Cooperative transportation

KW - Dispatching

KW - Guide path

KW - Loading unit

KW - Mobile ad hoc network

KW - Routing

KW - Traffic control

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Xing B, Gao WJ, Battle K, Marwala T, Nelwamondo FV. Can ant algorithms make automated guided vehicle system more intelligent? A viewpoint from manufacturing environment. In 2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010. 2010. p. 3226-3234. 5642291. (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics). doi: 10.1109/ICSMC.2010.5642291

Can ant algorithms make automated guided vehicle system more intelligent? A viewpoint from manufacturing environment

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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