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Ant Colony System algorithm solving a Thermal Generator Maintenance Scheduling Problem

Author:

Aristidis VlachosAuthors Info & Claims

Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology, Volume 24, Issue 4

Pages 713 - 723

Published: 01 July 2013 Publication History

Abstract

The maintenance scheduling problem of thermal generators is a large-scale combinatorial optimization with constraints. In this paper an Ant Colony System ACS algorithm, one of the Ant Colony Optimization ACO algorithms, is proposed for the maintenance scheduling problem. This ant colony optimization method allows the “agents” of an ant colony to deposit a small amount of pheromone trail to every path that has been explored, thus passing on to the other agents the information concerning the best solution. With the iterations we construct the final solution. This method is called “positive feedback”. The basic optimization routine is reinforced with the introduction of elitist ants who make the best solution stronger. The algorithm is applied to a real-scale system, and further experimenting leads to results that are commented.

References

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Digital Library

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Cited By

Pacini EIacono LMateos CGarcía Garino C(2019)A Bio-inspired Datacenter Selection Scheduler for Federated Clouds and Its Application to Frost PredictionJournal of Network and Systems Management10.1007/s10922-018-9481-027:3(688-729)Online publication date: 17-Jul-2019
https://dl.acm.org/doi/10.1007/s10922-018-9481-0
Liao WChen MYang X(2017)Joint optimization of preventive maintenance and production scheduling for parallel machines systemJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-16138532:1(913-923)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.3233/JIFS-161385

Ant Colony System algorithm solving a Thermal Generator Maintenance Scheduling Problem

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cover image Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology

Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology Volume 24, Issue 4

July 2013

226 pages

ISSN:1064-1246

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IOS Press

Netherlands

Publication History

Published: 01 July 2013

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Cited By

Pacini EIacono LMateos CGarcía Garino C(2019)A Bio-inspired Datacenter Selection Scheduler for Federated Clouds and Its Application to Frost PredictionJournal of Network and Systems Management10.1007/s10922-018-9481-027:3(688-729)Online publication date: 17-Jul-2019
https://dl.acm.org/doi/10.1007/s10922-018-9481-0
Liao WChen MYang X(2017)Joint optimization of preventive maintenance and production scheduling for parallel machines systemJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-16138532:1(913-923)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.3233/JIFS-161385

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