An Integrated Artificial Bee Colony Algorithm for Scheduling Jobs and Flexible Maintenance with Learning and Deteriorating Effects

Nesrine Touafek; Fatima Benbouzid-Si Tayeb; Asma Ladj; Alaeddine Dahamni; Riyadh Baghdadi

doi:10.1007/978-3-031-16014-1_51

An Integrated Artificial Bee Colony Algorithm for Scheduling Jobs and Flexible Maintenance with Learning and Deteriorating Effects

Nesrine Touafek, Fatima Benbouzid-Si Tayeb, Asma Ladj, Alaeddine Dahamni, Riyadh Baghdadi

Computer Science

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

Abstract

In this paper, we address two versions of the permutation flowshop scheduling problem (PFSP) with makespan minimization under availability constraints with learning and deteriorating effects. Availability constraints are due to flexible maintenance activities scheduled based on prognostics and health management (PHM) results. In the first study, human learning effect is considered and position-dependent model is applied to generate variable maintenance processing times. In the second one, besides learning effect, time-dependent machine deteriorating jobs are assumed. Since the PFSP is proven to be NP-complete, improved artificial bees colony algorithms were proposed. Intense computational experiments are carried out on Taillard’s well known benchmarks, to which we add both PHM and maintenance data. The results of comparison and experiments show the efficiency of our algorithms.

Original language	English (US)
Title of host publication	Computational Collective Intelligence - 14th International Conference, ICCCI 2022, Proceedings
Editors	Ngoc Thanh Nguyen, Adrianna Kozierkiewicz, Bogdan Trawiński, Yannis Manolopoulos, Richard Chbeir
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	647-659
Number of pages	13
ISBN (Print)	9783031160134
DOIs	https://doi.org/10.1007/978-3-031-16014-1_51
State	Published - 2022
Event	14th International Conference on Computational Collective Intelligence , ICCCI 2022 - Hammamet, Tunisia Duration: Sep 28 2022 → Sep 30 2022

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13501 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	14th International Conference on Computational Collective Intelligence , ICCCI 2022
Country/Territory	Tunisia
City	Hammamet
Period	9/28/22 → 9/30/22

Keywords

Artificial bee colony
Deteriorating effect
Flexible maintenance
Learning effect
Permutation flowshop scheduling problem
PHM

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-031-16014-1_51

Cite this

Touafek, N., Benbouzid-Si Tayeb, F., Ladj, A., Dahamni, A., & Baghdadi, R. (2022). An Integrated Artificial Bee Colony Algorithm for Scheduling Jobs and Flexible Maintenance with Learning and Deteriorating Effects. In N. T. Nguyen, A. Kozierkiewicz, B. Trawiński, Y. Manolopoulos, & R. Chbeir (Eds.), Computational Collective Intelligence - 14th International Conference, ICCCI 2022, Proceedings (pp. 647-659). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13501 LNAI). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-16014-1_51

An Integrated Artificial Bee Colony Algorithm for Scheduling Jobs and Flexible Maintenance with Learning and Deteriorating Effects. / Touafek, Nesrine; Benbouzid-Si Tayeb, Fatima; Ladj, Asma et al.
Computational Collective Intelligence - 14th International Conference, ICCCI 2022, Proceedings. ed. / Ngoc Thanh Nguyen; Adrianna Kozierkiewicz; Bogdan Trawiński; Yannis Manolopoulos; Richard Chbeir. Springer Science and Business Media Deutschland GmbH, 2022. p. 647-659 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13501 LNAI).

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

Touafek, N, Benbouzid-Si Tayeb, F, Ladj, A, Dahamni, A & Baghdadi, R 2022, An Integrated Artificial Bee Colony Algorithm for Scheduling Jobs and Flexible Maintenance with Learning and Deteriorating Effects. in NT Nguyen, A Kozierkiewicz, B Trawiński, Y Manolopoulos & R Chbeir (eds), Computational Collective Intelligence - 14th International Conference, ICCCI 2022, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13501 LNAI, Springer Science and Business Media Deutschland GmbH, pp. 647-659, 14th International Conference on Computational Collective Intelligence , ICCCI 2022, Hammamet, Tunisia, 9/28/22. https://doi.org/10.1007/978-3-031-16014-1_51

Touafek N, Benbouzid-Si Tayeb F, Ladj A, Dahamni A, Baghdadi R. An Integrated Artificial Bee Colony Algorithm for Scheduling Jobs and Flexible Maintenance with Learning and Deteriorating Effects. In Nguyen NT, Kozierkiewicz A, Trawiński B, Manolopoulos Y, Chbeir R, editors, Computational Collective Intelligence - 14th International Conference, ICCCI 2022, Proceedings. Springer Science and Business Media Deutschland GmbH. 2022. p. 647-659. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-16014-1_51

Touafek, Nesrine ; Benbouzid-Si Tayeb, Fatima ; Ladj, Asma et al. / An Integrated Artificial Bee Colony Algorithm for Scheduling Jobs and Flexible Maintenance with Learning and Deteriorating Effects. Computational Collective Intelligence - 14th International Conference, ICCCI 2022, Proceedings. editor / Ngoc Thanh Nguyen ; Adrianna Kozierkiewicz ; Bogdan Trawiński ; Yannis Manolopoulos ; Richard Chbeir. Springer Science and Business Media Deutschland GmbH, 2022. pp. 647-659 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{4462a3132c7b4233acfe0b2fabb5cf31,

title = "An Integrated Artificial Bee Colony Algorithm for Scheduling Jobs and Flexible Maintenance with Learning and Deteriorating Effects",

abstract = "In this paper, we address two versions of the permutation flowshop scheduling problem (PFSP) with makespan minimization under availability constraints with learning and deteriorating effects. Availability constraints are due to flexible maintenance activities scheduled based on prognostics and health management (PHM) results. In the first study, human learning effect is considered and position-dependent model is applied to generate variable maintenance processing times. In the second one, besides learning effect, time-dependent machine deteriorating jobs are assumed. Since the PFSP is proven to be NP-complete, improved artificial bees colony algorithms were proposed. Intense computational experiments are carried out on Taillard{\textquoteright}s well known benchmarks, to which we add both PHM and maintenance data. The results of comparison and experiments show the efficiency of our algorithms.",

keywords = "Artificial bee colony, Deteriorating effect, Flexible maintenance, Learning effect, Permutation flowshop scheduling problem, PHM",

author = "Nesrine Touafek and {Benbouzid-Si Tayeb}, Fatima and Asma Ladj and Alaeddine Dahamni and Riyadh Baghdadi",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 14th International Conference on Computational Collective Intelligence , ICCCI 2022 ; Conference date: 28-09-2022 Through 30-09-2022",

year = "2022",

doi = "10.1007/978-3-031-16014-1_51",

language = "English (US)",

isbn = "9783031160134",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "647--659",

editor = "Nguyen, {Ngoc Thanh} and Adrianna Kozierkiewicz and Bogdan Trawi{\'n}ski and Yannis Manolopoulos and Richard Chbeir",

booktitle = "Computational Collective Intelligence - 14th International Conference, ICCCI 2022, Proceedings",

address = "Germany",

}

TY - GEN

T1 - An Integrated Artificial Bee Colony Algorithm for Scheduling Jobs and Flexible Maintenance with Learning and Deteriorating Effects

AU - Touafek, Nesrine

AU - Benbouzid-Si Tayeb, Fatima

AU - Ladj, Asma

AU - Dahamni, Alaeddine

AU - Baghdadi, Riyadh

PY - 2022

Y1 - 2022

N2 - In this paper, we address two versions of the permutation flowshop scheduling problem (PFSP) with makespan minimization under availability constraints with learning and deteriorating effects. Availability constraints are due to flexible maintenance activities scheduled based on prognostics and health management (PHM) results. In the first study, human learning effect is considered and position-dependent model is applied to generate variable maintenance processing times. In the second one, besides learning effect, time-dependent machine deteriorating jobs are assumed. Since the PFSP is proven to be NP-complete, improved artificial bees colony algorithms were proposed. Intense computational experiments are carried out on Taillard’s well known benchmarks, to which we add both PHM and maintenance data. The results of comparison and experiments show the efficiency of our algorithms.

AB - In this paper, we address two versions of the permutation flowshop scheduling problem (PFSP) with makespan minimization under availability constraints with learning and deteriorating effects. Availability constraints are due to flexible maintenance activities scheduled based on prognostics and health management (PHM) results. In the first study, human learning effect is considered and position-dependent model is applied to generate variable maintenance processing times. In the second one, besides learning effect, time-dependent machine deteriorating jobs are assumed. Since the PFSP is proven to be NP-complete, improved artificial bees colony algorithms were proposed. Intense computational experiments are carried out on Taillard’s well known benchmarks, to which we add both PHM and maintenance data. The results of comparison and experiments show the efficiency of our algorithms.

KW - Artificial bee colony

KW - Deteriorating effect

KW - Flexible maintenance

KW - Learning effect

KW - Permutation flowshop scheduling problem

KW - PHM

UR - http://www.scopus.com/inward/record.url?scp=85140458127&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85140458127&partnerID=8YFLogxK

U2 - 10.1007/978-3-031-16014-1_51

DO - 10.1007/978-3-031-16014-1_51

M3 - Conference contribution

AN - SCOPUS:85140458127

SN - 9783031160134

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 647

EP - 659

BT - Computational Collective Intelligence - 14th International Conference, ICCCI 2022, Proceedings

A2 - Nguyen, Ngoc Thanh

A2 - Kozierkiewicz, Adrianna

A2 - Trawiński, Bogdan

A2 - Manolopoulos, Yannis

A2 - Chbeir, Richard

PB - Springer Science and Business Media Deutschland GmbH

T2 - 14th International Conference on Computational Collective Intelligence , ICCCI 2022

Y2 - 28 September 2022 through 30 September 2022

ER -