- -

Iterated Greedy methods for the distributed permutation flowshop scheduling problem

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by

Statistics

Iterated Greedy methods for the distributed permutation flowshop scheduling problem

Show full item record

Ruiz García, R.; Pan, Q.; Naderi, B. (2019). Iterated Greedy methods for the distributed permutation flowshop scheduling problem. Omega. 83:213-222. https://doi.org/10.1016/j.omega.2018.03.004

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/159840

Files in this item

Item Metadata

Title: Iterated Greedy methods for the distributed permutation flowshop scheduling problem
Author: Ruiz García, Rubén Pan, Quan-Ke Naderi, Bahman
UPV Unit: Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat
Issued date:
Abstract:
[EN] Large manufacturing firms operate more than one production center. As a result, in relation to scheduling problems, which factory manufactures which product is an important consideration. In this paper we study an ...[+]
Subjects: Distributed flowshop , Makespan , Metaheuristics , Iterated Greedy
Copyrigths: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
Source:
Omega. (issn: 0305-0483 )
DOI: 10.1016/j.omega.2018.03.004
Publisher:
Elsevier
Publisher version: https://doi.org/10.1016/j.omega.2018.03.004
Project ID:
info:eu-repo/grantAgreement/NSFC//51575212/
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-094940-B-I00/ES/OPTIMIZACION DE OPERACIONES EN TERMINALES PORTUARIAS/
Thanks:
Ruben Ruiz is partially supported by the Spanish Ministry of Economy and Competitiveness, under the project "SCHEYARD - Optimization of Scheduling Problems in Container Yards" (No. DPI2015-65895-R) financed by FEDER funds. ...[+]
Type: Artículo

References

Behnamian, J., & Fatemi Ghomi, S. M. T. (2014). A survey of multi-factory scheduling. Journal of Intelligent Manufacturing, 27(1), 231-249. doi:10.1007/s10845-014-0890-y

Chan, H. K., & Chung, S. H. (2013). Optimisation approaches for distributed scheduling problems. International Journal of Production Research, 51(9), 2571-2577. doi:10.1080/00207543.2012.755345

Deng, J., & Wang, L. (2017). A competitive memetic algorithm for multi-objective distributed permutation flow shop scheduling problem. Swarm and Evolutionary Computation, 32, 121-131. doi:10.1016/j.swevo.2016.06.002 [+]
Behnamian, J., & Fatemi Ghomi, S. M. T. (2014). A survey of multi-factory scheduling. Journal of Intelligent Manufacturing, 27(1), 231-249. doi:10.1007/s10845-014-0890-y

Chan, H. K., & Chung, S. H. (2013). Optimisation approaches for distributed scheduling problems. International Journal of Production Research, 51(9), 2571-2577. doi:10.1080/00207543.2012.755345

Deng, J., & Wang, L. (2017). A competitive memetic algorithm for multi-objective distributed permutation flow shop scheduling problem. Swarm and Evolutionary Computation, 32, 121-131. doi:10.1016/j.swevo.2016.06.002

Fernandez-Viagas, V., & Framinan, J. M. (2014). A bounded-search iterated greedy algorithm for the distributed permutation flowshop scheduling problem. International Journal of Production Research, 53(4), 1111-1123. doi:10.1080/00207543.2014.948578

Fernandez-Viagas, V., Ruiz, R., & Framinan, J. M. (2017). A new vision of approximate methods for the permutation flowshop to minimise makespan: State-of-the-art and computational evaluation. European Journal of Operational Research, 257(3), 707-721. doi:10.1016/j.ejor.2016.09.055

Framinan, J. M., Gupta, J. N. D., & Leisten, R. (2004). A review and classification of heuristics for permutation flow-shop scheduling with makespan objective. Journal of the Operational Research Society, 55(12), 1243-1255. doi:10.1057/palgrave.jors.2601784

Gao, J., & Chen, R. (2011). A hybrid genetic algorithm for the distributed permutation flowshop scheduling problem. International Journal of Computational Intelligence Systems, 4(4), 497-508. doi:10.1080/18756891.2011.9727808

Gao, J., Chen, R., & Deng, W. (2013). An efficient tabu search algorithm for the distributed permutation flowshop scheduling problem. International Journal of Production Research, 51(3), 641-651. doi:10.1080/00207543.2011.644819

Garey, M. R., Johnson, D. S., & Sethi, R. (1976). The Complexity of Flowshop and Jobshop Scheduling. Mathematics of Operations Research, 1(2), 117-129. doi:10.1287/moor.1.2.117

Graham, R. L., Lawler, E. L., Lenstra, J. K., & Kan, A. H. G. R. (1979). Optimization and Approximation in Deterministic Sequencing and Scheduling: a Survey. Annals of Discrete Mathematics, 287-326. doi:10.1016/s0167-5060(08)70356-x

Gupta, J. N. D., & Stafford, E. F. (2006). Flowshop scheduling research after five decades. European Journal of Operational Research, 169(3), 699-711. doi:10.1016/j.ejor.2005.02.001

Hatami, S., Ruiz, R., & Andrés-Romano, C. (2013). The Distributed Assembly Permutation Flowshop Scheduling Problem. International Journal of Production Research, 51(17), 5292-5308. doi:10.1080/00207543.2013.807955

Hatami, S., Ruiz, R., & Andrés-Romano, C. (2015). Heuristics and metaheuristics for the distributed assembly permutation flowshop scheduling problem with sequence dependent setup times. International Journal of Production Economics, 169, 76-88. doi:10.1016/j.ijpe.2015.07.027

Reza Hejazi *, S., & Saghafian, S. (2005). Flowshop-scheduling problems with makespan criterion: a review. International Journal of Production Research, 43(14), 2895-2929. doi:10.1080/0020754050056417

Johnson, S. M. (1954). Optimal two- and three-stage production schedules with setup times included. Naval Research Logistics Quarterly, 1(1), 61-68. doi:10.1002/nav.3800010110

Kendall, G., Bai, R., Błazewicz, J., De Causmaecker, P., Gendreau, M., John, R., … Yee, A. (2016). Good Laboratory Practice for optimization research. Journal of the Operational Research Society, 67(4), 676-689. doi:10.1057/jors.2015.77

Lin, S.-W., Ying, K.-C., & Huang, C.-Y. (2013). Minimising makespan in distributed permutation flowshops using a modified iterated greedy algorithm. International Journal of Production Research, 51(16), 5029-5038. doi:10.1080/00207543.2013.790571

MACCARTHY, B. L., & LIU, J. (1993). Addressing the gap in scheduling research: a review of optimization and heuristic methods in production scheduling. International Journal of Production Research, 31(1), 59-79. doi:10.1080/00207549308956713

MCKAY, K., PINEDO, M., & WEBSTER, S. (2009). PRACTICE-FOCUSED RESEARCH ISSUES FOR SCHEDULING SYSTEMS*. Production and Operations Management, 11(2), 249-258. doi:10.1111/j.1937-5956.2002.tb00494.x

McKay, K. N., Safayeni, F. R., & Buzacott, J. A. (1988). Job-Shop Scheduling Theory: What Is Relevant? Interfaces, 18(4), 84-90. doi:10.1287/inte.18.4.84

Mladenović, N., & Hansen, P. (1997). Variable neighborhood search. Computers & Operations Research, 24(11), 1097-1100. doi:10.1016/s0305-0548(97)00031-2

Naderi, B., & Ruiz, R. (2010). The distributed permutation flowshop scheduling problem. Computers & Operations Research, 37(4), 754-768. doi:10.1016/j.cor.2009.06.019

Naderi, B., & Ruiz, R. (2014). A scatter search algorithm for the distributed permutation flowshop scheduling problem. European Journal of Operational Research, 239(2), 323-334. doi:10.1016/j.ejor.2014.05.024

Nawaz, M., Enscore, E. E., & Ham, I. (1983). A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem. Omega, 11(1), 91-95. doi:10.1016/0305-0483(83)90088-9

Pan, Q.-K., & Ruiz, R. (2014). An effective iterated greedy algorithm for the mixed no-idle permutation flowshop scheduling problem. Omega, 44, 41-50. doi:10.1016/j.omega.2013.10.002

Pan, Q.-K., Ruiz, R., & Alfaro-Fernández, P. (2017). Iterated search methods for earliness and tardiness minimization in hybrid flowshops with due windows. Computers & Operations Research, 80, 50-60. doi:10.1016/j.cor.2016.11.022

Rad, S. F., Ruiz, R., & Boroojerdian, N. (2009). New high performing heuristics for minimizing makespan in permutation flowshops. Omega, 37(2), 331-345. doi:10.1016/j.omega.2007.02.002

Reisman, A., Kumar, A., & Motwani, J. (1997). Flowshop scheduling/sequencing research: a statistical review of the literature, 1952-1994. IEEE Transactions on Engineering Management, 44(3), 316-329. doi:10.1109/17.618173

Ribas, I., Companys, R., & Tort-Martorell, X. (2017). Efficient heuristics for the parallel blocking flow shop scheduling problem. Expert Systems with Applications, 74, 41-54. doi:10.1016/j.eswa.2017.01.006

Rifai, A. P., Nguyen, H.-T., & Dawal, S. Z. M. (2016). Multi-objective adaptive large neighborhood search for distributed reentrant permutation flow shop scheduling. Applied Soft Computing, 40, 42-57. doi:10.1016/j.asoc.2015.11.034

Ruiz, R., & Maroto, C. (2005). A comprehensive review and evaluation of permutation flowshop heuristics. European Journal of Operational Research, 165(2), 479-494. doi:10.1016/j.ejor.2004.04.017

Ruiz, R., & Stützle, T. (2007). A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem. European Journal of Operational Research, 177(3), 2033-2049. doi:10.1016/j.ejor.2005.12.009

Sörensen, K. (2013). Metaheuristics-the metaphor exposed. International Transactions in Operational Research, 22(1), 3-18. doi:10.1111/itor.12001

Taillard, E. (1990). Some efficient heuristic methods for the flow shop sequencing problem. European Journal of Operational Research, 47(1), 65-74. doi:10.1016/0377-2217(90)90090-x

Taillard, E. (1993). Benchmarks for basic scheduling problems. European Journal of Operational Research, 64(2), 278-285. doi:10.1016/0377-2217(93)90182-m

Urlings, T., Ruiz, R., & Stützle, T. (2010). Shifting representation search for hybrid flexible flowline problems. European Journal of Operational Research, 207(2), 1086-1095. doi:10.1016/j.ejor.2010.05.041

Wang, K., Huang, Y., & Qin, H. (2016). A fuzzy logic-based hybrid estimation of distribution algorithm for distributed permutation flowshop scheduling problems under machine breakdown. Journal of the Operational Research Society, 67(1), 68-82. doi:10.1057/jors.2015.50

Wang, S., Wang, L., Liu, M., & Xu, Y. (2013). An effective estimation of distribution algorithm for solving the distributed permutation flow-shop scheduling problem. International Journal of Production Economics, 145(1), 387-396. doi:10.1016/j.ijpe.2013.05.004

Xu, Y., Wang, L., Wang, S., & Liu, M. (2013). An effective hybrid immune algorithm for solving the distributed permutation flow-shop scheduling problem. Engineering Optimization, 46(9), 1269-1283. doi:10.1080/0305215x.2013.827673

[-]

recommendations

 

This item appears in the following Collection(s)

Show full item record