An estimation of distribution algorithm with guided mutation for a complex flow shop scheduling problem

Abdellah Salhi; José Antonio Vázquez Rodríguez; Qingfu Zhang

doi:10.1145/1276958.1277076

An estimation of distribution algorithm with guided mutation for a complex flow shop scheduling problem

Abdellah Salhi
, José Antonio Vázquez Rodríguez
, Qingfu Zhang

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

32 Citations (Scopus)

Abstract

An Estimation of Distribution Algorithm (EDA) is proposed toapproach the Hybrid Flow Shop with Sequence Dependent Setup Times and Uniform Machines in parallel (HFS-SDST-UM) problem. The latter motivated by the needs of a real world company. The proposed EDA implements a fairly new mechanism to improve the search of more traditional EDAs. This is the Guided Mutation (GM). EDA-GM generates new solutions by using the information from a probability model, as all EDAs, and the local information from a good known solution. The approach is tested on several instances of HFS-SDST-UM and compared with adaptations of meta-heuristics designed for very similarproblems. Encouraging results are reported. Copyright 2007 ACM.

Original language	English
Title of host publication	Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference
Pages	570-576
DOIs	https://doi.org/10.1145/1276958.1277076
Publication status	Published - 2007
Externally published	Yes
Event	9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007 - London, United Kingdom Duration: 7 Jul 2007 → 11 Jul 2007

Conference

Conference	9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007
Place	United Kingdom
City	London
Period	7/07/07 → 11/07/07

Research Keywords

Combinatorial optimization
Metaheuristics
Timetabling and scheduling

Access Output

10.1145/1276958.1277076

Other Access Options

Check CityUHK Library

Permanent Link

Right click to copy link

Cite this

@inproceedings{964d082ff6f04ede8090de8671ad4108,

title = "An estimation of distribution algorithm with guided mutation for a complex flow shop scheduling problem",

abstract = "An Estimation of Distribution Algorithm (EDA) is proposed toapproach the Hybrid Flow Shop with Sequence Dependent Setup Times and Uniform Machines in parallel (HFS-SDST-UM) problem. The latter motivated by the needs of a real world company. The proposed EDA implements a fairly new mechanism to improve the search of more traditional EDAs. This is the Guided Mutation (GM). EDA-GM generates new solutions by using the information from a probability model, as all EDAs, and the local information from a good known solution. The approach is tested on several instances of HFS-SDST-UM and compared with adaptations of meta-heuristics designed for very similarproblems. Encouraging results are reported. Copyright 2007 ACM.",

keywords = "Combinatorial optimization, Metaheuristics, Timetabling and scheduling",

author = "Abdellah Salhi and Rodr{\'i}guez, \{Jos{\'e} Antonio V{\'a}zquez\} and Qingfu Zhang",

year = "2007",

doi = "10.1145/1276958.1277076",

language = "English",

isbn = "1595936971",

pages = "570--576",

booktitle = "Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference",

note = "9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007 ; Conference date: 07-07-2007 Through 11-07-2007",

}

Salhi, A, Rodríguez, JAV & Zhang, Q 2007, An estimation of distribution algorithm with guided mutation for a complex flow shop scheduling problem. in Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference. pp. 570-576, 9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007, London, United Kingdom, 7/07/07. https://doi.org/10.1145/1276958.1277076

An estimation of distribution algorithm with guided mutation for a complex flow shop scheduling problem. / Salhi, Abdellah; Rodríguez, José Antonio Vázquez; Zhang, Qingfu.
Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference. 2007. p. 570-576.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - An estimation of distribution algorithm with guided mutation for a complex flow shop scheduling problem

AU - Salhi, Abdellah

AU - Rodríguez, José Antonio Vázquez

AU - Zhang, Qingfu

PY - 2007

Y1 - 2007

N2 - An Estimation of Distribution Algorithm (EDA) is proposed toapproach the Hybrid Flow Shop with Sequence Dependent Setup Times and Uniform Machines in parallel (HFS-SDST-UM) problem. The latter motivated by the needs of a real world company. The proposed EDA implements a fairly new mechanism to improve the search of more traditional EDAs. This is the Guided Mutation (GM). EDA-GM generates new solutions by using the information from a probability model, as all EDAs, and the local information from a good known solution. The approach is tested on several instances of HFS-SDST-UM and compared with adaptations of meta-heuristics designed for very similarproblems. Encouraging results are reported. Copyright 2007 ACM.

AB - An Estimation of Distribution Algorithm (EDA) is proposed toapproach the Hybrid Flow Shop with Sequence Dependent Setup Times and Uniform Machines in parallel (HFS-SDST-UM) problem. The latter motivated by the needs of a real world company. The proposed EDA implements a fairly new mechanism to improve the search of more traditional EDAs. This is the Guided Mutation (GM). EDA-GM generates new solutions by using the information from a probability model, as all EDAs, and the local information from a good known solution. The approach is tested on several instances of HFS-SDST-UM and compared with adaptations of meta-heuristics designed for very similarproblems. Encouraging results are reported. Copyright 2007 ACM.

KW - Combinatorial optimization

KW - Metaheuristics

KW - Timetabling and scheduling

UR - https://www.scopus.com/pages/publications/34548077216

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-34548077216&origin=recordpage

U2 - 10.1145/1276958.1277076

DO - 10.1145/1276958.1277076

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 1595936971

SN - 9781595936974

SP - 570

EP - 576

BT - Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference

T2 - 9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007

Y2 - 7 July 2007 through 11 July 2007

ER -

An estimation of distribution algorithm with guided mutation for a complex flow shop scheduling problem

Abstract

Conference

Research Keywords

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Cite this