research-article

Iterated greedy algorithms for the hybrid flowshop scheduling with total flow time minimization

Authors:

M. Fatih Tasgetiren,

Deniz Türsel Eliiyi,

Quan-Ke PanAuthors Info & Claims

GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference

Pages 379 - 385

https://doi.org/10.1145/3205455.3205500

Published: 02 July 2018 Publication History

Abstract

The hybrid flowshop scheduling problem (HFSP) has been extensively studied in the literature, due to its complexity and real-life applicability. Various exact and heuristic algorithms have been developed for the HFSP, and most consider makespan as the only criterion. The studies on HFSP with the objective of minimizing total flow time have been rather limited. This paper presents a mathematical model and efficient iterated greedy algorithms, IG and IG_ALL, for the HFSP with total flow time criterion. In order to evaluate the performance of the proposed IG algorithms, the well-known HFSP benchmark suite from the literature is used. As the problem is NP-hard, the proposed mathematical model is solved for all 87 instances under a time limit on CPLEX. Optimal results are obtained for some of these instances. The performance of the IG algorithms is measured by comparisons with these time-limited CPLEX results of the mathematical model. Computational results show that the proposed IG algorithms perform very well in terms of solution time and quality. To the best of our knowledge, for the first time in the literature, the results of flow time criterion have been reported for the HFSP benchmark suite.

References

[1]

S.M. Johnson, 1954. Optimal two-and three-stage production schedules with setup times included. Naval Research Logistics Quarterly. 1:61--8.

[2]

I. Ribas, R. Leisten, J.M. Framinan, 2010. Review and classification of hybrid flowshop scheduling problems from a production system and a solutions procedure perspective. Computers & Operations Research. 37: 1439--54.

Digital Library

[3]

QK. Pan, L. Wang, K. Mao, JH. Zhao, M. Zhang, 2013. An effective artificial bee colony algorithm for a real-world hybrid flowshop problem in steel making process. IEEE Transactions on Automation Science and Engineering. 10(2): 307--22.

[4]

HD. Sherah, SC Sarin, MS. Kodialam, 1990. Models and algorithms for a two-stage production process. Production Planning and Control. 1 (1): 27--39.

[5]

J. Grabowski, J. Pempera, 2000. Sequencing of jobs in some production system. European Journal of Operational Research. 125 (3): 535--550.

[6]

JR. Wittrock, 1988. An adaptable scheduling algorithm for flexible flow lines. Operations Research. 36 (3): 445--453.

Digital Library

[7]

CY. Liu, SC. Chang, 2000. Scheduling flexible flowshops with sequence dependent setup effects. IEEE Transactions on Robotics and Automation. 16 (4): 408--419.

[8]

ZH. Jin, K. Ohno, T. Ito, SE. Elmaghraby, 2002. Scheduling hybrid flowshops in printed circuit board assembly lines. Production and Operations Management. 11 (2): 216--230.

[9]

R. Ruiz, J.A. Vazquez Rodriguez, 2010. The hybrid flowshop scheduling problem. European Journal of Operational Research. 205: 1--18.

[10]

C. Rajendran, D. Chaudhuri, 1992. An efficient heuristic approach to the scheduling of jobs in a flow shop. European Journal of Operational Research. 61:318--325.

[11]

A. Vignier, D. Dardilhac, D. Dezalay, C. Proust, 1996. A branch and bound approach to minimize the total completeion time in a k-stage hybrid flowshop, in: Proceedings of the Fifth International Conference on Emerging Technologies and Factory Automation (ETFA '96) IEEE Press. 215--220.

[12]

M. Azizoğlu, E. Çakmak, S. Kondakci, 2001. A flexible flowshop problem with total flow time minimization. European Journal of Operational Research. 132: 528--538.

[13]

L.X. Tang, H. Xuan, J.Y. Liu, 2006. A new lagrangian relaxation algorithm for hybrid flowshop scheduling to minimize total weighted completion time. Computers & Operations Research. 33: 3344--3359.

Digital Library

[14]

E. Nowicki, C. Smutnick, 1998. The flow shop with parallel machines: a tabu search approach. European Journal of Operational Research. 106: 226--253.

[15]

K. Alaykyran, O. Engin, A. Doyen, 2007. Using ant colony optimization to solve hybrid flow shop scheduling problems. International Journal of Advanced Manufacturing Technology. 35: 541--550.

[16]

C. Kahraman, O. Engin, I. Kaya, M.K. Yilmaz, 2008. An application of effective genetic algorithms for solving hybrid flow shop scheduling problems. International Journal of Computational Intelligence Systems. 1 (2): 134--147.

[17]

Z. Jin, Z. Yang, T. Ito, 2006. Metaheuristic algorithms for the multistage hybrid flowshop scheduling problem. International Journal of Production Economics. 100: 322--334.

[18]

C.J. Liao, E. Tjandradjaj, T.P. Chung, 2012. An approach using particle swarm optimization and bottleneck heuristic to solve flowshop scheduling problem. Applied Soft Computing. 12: 1755--1764.

Digital Library

[19]

D. Kizilay, M.F. Tasgetiren, Q. Pan, L. Wang, 2014. An Iterated Greedy Algorithm for the Hybrid Flowshop Problem with Makespan Criterion. Computational Intelligence in Production and Logistics Systems (CIPLS), 2014 IEEE Symposium on. 16--23.

[20]

S. Brah, L. L. Loo, 1999. Heuristics for scheduling in a flow Shop with multiple processors. European Journal of Operational Research. 113: 113--122.

[21]

A. Allahverdi, F.S. Al-Anzi, 2006. Scheduling multi-stage parallel-processor services to minimize average response time. Journal of the Operational Research Society. 2006; 57:101.

[22]

C.Y. Low, 2005. Simulated annealing heuristic for flow shop scheduling problems with unrelated parallel machines. Computers and Operations Research. 32 (8): 2013--2025.

Digital Library

[23]

B. Naderi, M. Zandieh, A.K.G. Balagh, V. Roshanaei, 2009. An improved simulated annealing for hybrid flowshops with sequence-dependent setup and transportation times to minimize total completion and total tardiness. Expert Systems with Applications. 36: 9625--9633.

Digital Library

[24]

Q. Niu, T. Zhou, M. Fei, B. Wang, 2012. An efficient quantum immune algorithm to minimize mean flow time for hybrid flow shop problems. Mathematics and Computers in Simulation. 84: 1--25.

Digital Library

[25]

Q. Pan, Y. Dang, 2014. An improved migrating birds optimisation for a hybrid flowshop scheduling with total flowtime minimization. Information Sciences. 277: 643--655

[26]

J. Carlier, E. Neron, 2000. An exact method for solving the multiprocessor flowshop. R.A.I.R.O. Operations Research. 34: 1--25.

[27]

A. Vignier, JC. Billaut, C. Proust, 1999. Hybrid flowshop scheduling problems: state of the art. Rairo - Recherche Operationnelle --- Operations Research. 33 (2): 117--83.

[28]

RL. Graham, EL. Lawler, J.K. Lenstra, AHG. Kan Rinnooy, 1979. Optimization and approximation in deterministic sequencing and scheduling: a survey. Ann Discrete Math. 5: 287--326.

[29]

M.S. Garey, D.S. Johnson, R. Sethi, 1976. The complexity of flowshop and jobshop scheduling. Mathematics of Operations Research. 1:117--129.

Digital Library

[30]

R. Ruiz, T. Stützle, 2007. A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem. European Journal of Operational Research. 177(3): 2033 --49

[31]

M. Nawaz, Jr. E.E. Enscore, I. Ham, 1983. A heuristic algorithm for the m-machine, n-job flowshop sequencing problem. OMEGA. 11(1):91--95

[32]

M.F. Tasgetiren, D. Kizilay, QK. Pan, PN. Suganthan, 2017. Iterated greedy algorithms for the blocking flowshop scheduling problem with the makespan criterion. Computers and Operations Research. 77: 111--126.

Digital Library

[33]

M.F. Tasgetiren, QK. Pan, D. Kizilay, K. Gao, 2016. A variable block insertion heuristic for the blocking flowshop scheduling problem with total flowtime criterion. Algorithms. 9 (4): 71.

[34]

M.F. Tasgetiren, QK. Pan, PN. Suganthan, A. Oner, 2013. A discrete artificial bee colony algorithm for the no-idle permutation flowshop scheduling problem with the total tardiness criterion. Applied Mathematical Modelling. 37: 675 8--6779.

[35]

I. Osman, C. Potts, 1989. Simulated annealing for permutation flow-shop scheduling. OMEGA. 17(6), 551--557

[36]

J. Dubois-Lacoste, F. Pagnozzi, T. Stützle, 2017. An iterated greedy algorithm with optimization of partial solutions for the makespan permutation flowshop problem. Computers and Operations Research. 81: 160--166

Digital Library

[37]

CJ. Liao, E. Tjandradjaj, TP. Chung, 2012. An approach using particle swarm optimization and bottleneck heuristic to solve flowshop scheduling problem. Applied Soft Computing. 12:1755--64.

Digital Library

Cited By

Lu YTang QPan QZhao LZhu Y(2023)A Heuristic-Based Adaptive Iterated Greedy Algorithm for Lot-Streaming Hybrid Flow Shop Scheduling Problem with Consistent and Intermingled Sub-LotsSensors10.3390/s2305280823:5(2808)Online publication date: 3-Mar-2023
https://doi.org/10.3390/s23052808
Van Den Houten Kde Weerdt MTax DFreydell EChristoupoulou ENati A(2023)Rolling-Horizon Simulation Optimization For A Multi-Objective Biomanufacturing Scheduling Problem2023 Winter Simulation Conference (WSC)10.1109/WSC60868.2023.10408070(1912-1923)Online publication date: 10-Dec-2023
https://doi.org/10.1109/WSC60868.2023.10408070
He YZhang J(2023)Research on Hybrid Flow-Shop Scheduling Problem Based on Seeker Optimization Algorithm2023 China Automation Congress (CAC)10.1109/CAC59555.2023.10450717(2866-2871)Online publication date: 17-Nov-2023
https://doi.org/10.1109/CAC59555.2023.10450717
Show More Cited By

Index Terms

Iterated greedy algorithms for the hybrid flowshop scheduling with total flow time minimization
1. Theory of computation
  1. Design and analysis of algorithms
    1. Approximation algorithms analysis
      1. Scheduling algorithms
    2. Mathematical optimization

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Abstract
The hybrid flowshop scheduling problem (HFSP) has been widely studied in the literature, as it has many real-life applications in industry. Even though many solution approaches have been presented for the HFSP with makespan criterion, ...
A hybrid iterated greedy algorithm for total tardiness minimization in permutation flowshops

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Iterated greedy algorithms for the blocking flowshop scheduling problem with makespan criterion

Recently, iterated greedy algorithms have been successfully applied to solve a variety of combinatorial optimization problems. This paper presents iterated greedy algorithms for solving the blocking flowshop scheduling problem (BFSP) with the makespan ...

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cover image ACM Conferences

GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference

July 2018

1578 pages

ISBN:9781450356183

DOI:10.1145/3205455

Editor:
Hernan Aguirre
Shinshu University
,
General Chair:
Keiki Takadama
The University of Electro-Communications

Copyright © 2018 ACM.

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Published: 02 July 2018

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GECCO '18: Genetic and Evolutionary Computation Conference

July 15 - 19, 2018

Kyoto, Japan

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Lu YTang QPan QZhao LZhu Y(2023)A Heuristic-Based Adaptive Iterated Greedy Algorithm for Lot-Streaming Hybrid Flow Shop Scheduling Problem with Consistent and Intermingled Sub-LotsSensors10.3390/s2305280823:5(2808)Online publication date: 3-Mar-2023
https://doi.org/10.3390/s23052808
Van Den Houten Kde Weerdt MTax DFreydell EChristoupoulou ENati A(2023)Rolling-Horizon Simulation Optimization For A Multi-Objective Biomanufacturing Scheduling Problem2023 Winter Simulation Conference (WSC)10.1109/WSC60868.2023.10408070(1912-1923)Online publication date: 10-Dec-2023
https://doi.org/10.1109/WSC60868.2023.10408070
He YZhang J(2023)Research on Hybrid Flow-Shop Scheduling Problem Based on Seeker Optimization Algorithm2023 China Automation Congress (CAC)10.1109/CAC59555.2023.10450717(2866-2871)Online publication date: 17-Nov-2023
https://doi.org/10.1109/CAC59555.2023.10450717
Zhao ZZhou MLiu S(2022)Iterated Greedy Algorithms for Flow-Shop Scheduling Problems: A TutorialIEEE Transactions on Automation Science and Engineering10.1109/TASE.2021.306299419:3(1941-1959)Online publication date: Jul-2022
https://doi.org/10.1109/TASE.2021.3062994
Öztop HTasgetiren MKandiller LPan Q(2020)A Novel General Variable Neighborhood Search through Q-Learning for No-Idle Flowshop Scheduling2020 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC48606.2020.9185556(1-8)Online publication date: 19-Jul-2020
https://dl.acm.org/doi/10.1109/CEC48606.2020.9185556
Seda MSeda PSedova J(2019)Job Shop Scheduling and Its Fuzzification Based on Operations and Disjunctive Graph Representations2019 11th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)10.1109/ICUMT48472.2019.8971003(1-5)Online publication date: Oct-2019
https://doi.org/10.1109/ICUMT48472.2019.8971003

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