Hybrid ant colony optimization and visibility studies applied to a job-shop scheduling problem

J. Heinonen; F. Pettersson

doi:10.1016/j.amc.2006.09.023

Hybrid ant colony optimization and visibility studies applied to a job-shop scheduling problem

J. Heinonen^*, F. Pettersson

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Tutkimustuotos: Lehtiartikkeli › Artikkeli › Tieteellinen › vertaisarvioitu

87 Sitaatiot (Scopus)

Abstrakti

A hybrid ant colony optimization (ACO) algorithm is applied to a well known job-shop scheduling problem: MT10 (Muth-Thompson). The ACO tries to preserve and improve existing solutions, and a postprocessing algorithm is applied to the tour of an ant upon its completion. Studies are performed to see what effect visibility has on the outcome with regards to the ACO part of the algorithm.

Alkuperäiskieli	Englanti
Sivut	989-998
Sivumäärä	10
Julkaisu	Applied Mathematics and Computation
Vuosikerta	187
Numero	2
DOI - pysyväislinkit	https://doi.org/10.1016/j.amc.2006.09.023
Tila	Julkaistu - 15 huhtikuuta 2007
OKM-julkaisutyyppi	A1 Julkaistu artikkeli, soviteltu

Pääsy asiakirjaan

10.1016/j.amc.2006.09.023

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Link to publication in Scopus

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Viittausmuodot

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abstract = "A hybrid ant colony optimization (ACO) algorithm is applied to a well known job-shop scheduling problem: MT10 (Muth-Thompson). The ACO tries to preserve and improve existing solutions, and a postprocessing algorithm is applied to the tour of an ant upon its completion. Studies are performed to see what effect visibility has on the outcome with regards to the ACO part of the algorithm.",

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KW - ACO

KW - Ant colony optimization

KW - Hybrid

KW - Job-shop scheduling

KW - Optimization

KW - Scheduling

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