Dispatching algorithm for production programming of flexible job-shop systems in the smart factory industry

In today highly competitive and globalized markets, an efficient use of production resources is necessary for manufacturing enterprises. In this research, the problem of scheduling and sequencing of manufacturing system is presented. A flexible job shop problem sequencing problem is analyzed in deta...

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Autores:
Ortiz Suarez, Miguel Angel
Betancourt Ferrer, Leidy Esperanza
Parra Negrete, Kevin Armando
De Felice, Fabio
Petrillo, Antonella
Tipo de recurso:
Article of journal
Fecha de publicación:
2018
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/1383
Acceso en línea:
https://hdl.handle.net/11323/1383
https://repositorio.cuc.edu.co/
Palabra clave:
Flexible Job-Shop System
Optimization
Reconfigurable System
Sequencing Problem
Rights
openAccess
License
Atribución – No comercial – Compartir igual
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oai_identifier_str oai:repositorio.cuc.edu.co:11323/1383
network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.eng.fl_str_mv Dispatching algorithm for production programming of flexible job-shop systems in the smart factory industry
title Dispatching algorithm for production programming of flexible job-shop systems in the smart factory industry
spellingShingle Dispatching algorithm for production programming of flexible job-shop systems in the smart factory industry
Flexible Job-Shop System
Optimization
Reconfigurable System
Sequencing Problem
title_short Dispatching algorithm for production programming of flexible job-shop systems in the smart factory industry
title_full Dispatching algorithm for production programming of flexible job-shop systems in the smart factory industry
title_fullStr Dispatching algorithm for production programming of flexible job-shop systems in the smart factory industry
title_full_unstemmed Dispatching algorithm for production programming of flexible job-shop systems in the smart factory industry
title_sort Dispatching algorithm for production programming of flexible job-shop systems in the smart factory industry
dc.creator.fl_str_mv Ortiz Suarez, Miguel Angel
Betancourt Ferrer, Leidy Esperanza
Parra Negrete, Kevin Armando
De Felice, Fabio
Petrillo, Antonella
dc.contributor.author.spa.fl_str_mv Ortiz Suarez, Miguel Angel
Betancourt Ferrer, Leidy Esperanza
Parra Negrete, Kevin Armando
De Felice, Fabio
Petrillo, Antonella
dc.subject.eng.fl_str_mv Flexible Job-Shop System
Optimization
Reconfigurable System
Sequencing Problem
topic Flexible Job-Shop System
Optimization
Reconfigurable System
Sequencing Problem
description In today highly competitive and globalized markets, an efficient use of production resources is necessary for manufacturing enterprises. In this research, the problem of scheduling and sequencing of manufacturing system is presented. A flexible job shop problem sequencing problem is analyzed in detail. After formulating this problem mathematically, a new model is proposed. This problem is not only theoretically interesting, but also practically relevant. An illustrative example is also conducted to demonstrate the applicability of the proposed model.
publishDate 2018
dc.date.accessioned.none.fl_str_mv 2018-11-20T01:36:23Z
dc.date.available.none.fl_str_mv 2018-11-20T01:36:23Z
dc.date.issued.none.fl_str_mv 2018-05-01
dc.type.spa.fl_str_mv Artículo de revista
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dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/article
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dc.type.version.spa.fl_str_mv info:eu-repo/semantics/acceptedVersion
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dc.identifier.issn.spa.fl_str_mv 02545330
dc.identifier.uri.spa.fl_str_mv https://hdl.handle.net/11323/1383
dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
dc.identifier.reponame.spa.fl_str_mv REDICUC - Repositorio CUC
dc.identifier.repourl.spa.fl_str_mv https://repositorio.cuc.edu.co/
identifier_str_mv 02545330
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url https://hdl.handle.net/11323/1383
https://repositorio.cuc.edu.co/
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.references.spa.fl_str_mv 430 Alvarez-Valdes, R., Fuertes, A., Tamarit, J. M., Giménez, G., & Ramos, R. (2005). A heuristic to schedule 431 flexible job-shop in a glass factory. European Journal of Operational Research, 165(2005), 525–534. 432 Baker, K. R. (2005). Elements of sequencing and scheduling. Hanover, NH: Tuck School of Business. 433 Barrios, M. A. O., Caballero, J. E., & Sánchez, F. S. (2015). A methodology for the creation of integrated service 434 networks in outpatient internal medicine. In Ambient intelligence for health (pp. 247–257). Springer. 435 Bozek, A., & Wysocki, M. (2015). Flexible job shop with continuous material flow. International Journal of 436 Production Research, 53(4), 1273–1290. 437 Brandimarte, P. (1993). Routing and scheduling in a flexible job shop by Tabu search. Annals of Operations 438 Research, 41(3), 157–183. 439 Calleja, G., & Pastor, R. (2014). A dispatching algorithm for flexible job-shop scheduling with transfer batches: 440 An industrial application. Production Planning & Control, 25(2), 93–109. 441 De Felice, F., & Petrillo, A. (2013). Simulation approach for the optimization of the layout in a manufacturing 442 firm. 24th IASTED international conference on modelling and simulation, MS 2013; Banff, AB; Canada; 443 17 July 2013 through 19 July 2013 (pp. 152–161). 444 Demir, Y., & I¸sleyen, S. K. (2014). An effective genetic algorithm for flexible job-shop scheduling with 445 overlapping in operations. International Journal of Production Research, 52(13), 3905–3921. 446 Digiesi, S., Mossa, G., & Mummolo, G. (2013). A sustainable order quantity model under uncertain product 447 demand. 7th IFAC conference on manufacturing modelling, management, and control, MIM 2013 (pp. 448 664–669). Saint Petersburg; Russian Federation; 19 June–21 June. 449 Fattahi, F., & Fallahi, A. (2010). Dynamic scheduling in flexible job shop systems by considering simultane450 ously efficiency and stability. CIRP Journal of Manufacturing Science and Technology, 2, 114–123. 451 Fattahi, P., Hosseini, S. M. H., Jolai, F., & Tavakkoli-Moghaddam, R. (2014). A branch and bound algorithm 452 for hybrid flow shop scheduling problem with setup time and assembly operations. Applied Mathematical 453 Modelling, 38, 119–134. 454 Gholami, O., & Sotskov, Y. N. (2014). Solving parallel machines job-shop scheduling problems by an adaptive 455 algorithm. International Journal of Production Research, 52(13), 3888–3904. 456 Guo, W. J. (2006). Algorithms for two-stage flexible flow shop scheduling with fuzzy processing times. NanJing: 457 NanJing University of Science & Technology. 458 Hassin, R., & Shani, M. (2005). Machine scheduling with earliness, tardiness and nonexecution penalties. 459 Computers & Operations Research, 32, 683–705. 460 Herazo-Padilla, N., Montoya-Torres, J. R., Isaza, S. N., & Alvarado-Valencia, J. (2015). Simulation461 optimization approach for the stochastic location-routing problem. Journal of Simulation, 9(4), 296–311. 462 Hildebrandt, T., Heger, J., & Scholz-Reiter, B. (2010). Towards improved dispatching rules for complex shop 463 floor scenarios—A genetic programming approach. GECCO’10, July 7–11, 2010. Portland, Oregon, 464 USA. 465 Hu, H. (2015). Adaptive scheduling model in hybrid flowshop production control using petri net. International 466 Journal of Control and Automation, 8(1), 233–242. 467 Jansen K, Mastrolilli M, & Solis-Oba R, (2000). Approximation algorithms for Flexible Job Shop Problems. 468 In: Lecture notes in computer science, Vol. 1776. Proceedings of the fourth Latin American symposium 469 on theoretical informatics (pp. 68–77). Berlin: Springer. 470 Jungwattanakit, J., Reodecha, M., Chaovalitwongse, P., & Werner, F. (2009). A comparison of scheduling 471 algorithms for flexible flow shop problems with unrelated parallel machines, setup times, and dual 472 criteria. Computers and Operations Research, 36(2), 358–378. 473 Kacem, I., Hammadi, S., & Borne, P. (2002). Pareto-optimality Approach for Flexible Job-shop Scheduling 474 Problems: Hybridization of Evolutionary Algorithms and Fuzzy Logic. Journal of Mathematics and 475 Computers in Simulation 476 Karimi-Nasab, M., & Modarres, M. (2015). Lot sizing and job shop scheduling with compressible process 477 times: A cut and branch approach. Computers & Industrial Engineering, 85, 196–205. 478 Kurz, M. E., & Askin, R. G. (2004). Scheduling flexible flow lines with sequence dependent setup times. 479 European Journal of Operational Research, 159(1), 66–82. 480 Logendran, R., Carson, S., & Hanson, E. (2005). Grouping scheduling in flexible flow shops. International 481 Journal of Production Economics, 96(2), 143–155. 482 Pezzella, F., Morganti, G., & Ciaschetti, G. (2008). A genetic algorithm for the Flexible Job-shop Scheduling 483 Problem. Computers & Operations Research, 35, 3202–3212. 484 Pinedo, M. (2001). Scheduling: Theory, algorithms, and systems. Upper Saddle River, NJ: Prentice Hall. 485 Prot, D., Bellenguez-Morineau, O., & Lahlou, C. (2013). New complexity results for parallel identical machine 486 scheduling problems with preemption, release dates and regular criteria. European Journal of Operational 487 Research, 231, 282–287. 488 Riane, F., Artiba, A., & Elmaghraby, S. E. (2002). Sequencing a hybrid two-stage flow shop with dedicated 489 machines. Int. J. Prod. Res., 40, 4353–4380. 490 Shen, X.-N., & Yao, X. (2015). Mathematical modeling and multi-objective evolutionary algorithms applied 491 to dynamic flexible job shop scheduling problems. Information Sciences, 298, 198–224. 492 Sotskov, Y. N., & Gholami, O. (2015). Mixed graph model and algorithms for parallel-machine job-shop 493 scheduling problems. International Journal of Production Research, 55(6), 1549–1564. 494 Sun, D.-H., He, W., Zheng, L.-J., & Liao, X.-Y. (2014). Scheduling flexible job shop problem subject to machine 495 breakdown with game theory. International Journal of Production Research, 52(13), 3858–3876. 496 Türkylmaz, A., & Bulkan, S. (2015). A hybrid algorithm for total tardiness minimization in flexible job shop: 497 Genetic algorithm with parallel VNS execution. International Journal of Production Research, 53(6), 498 1832–1848. 499 Wang, S., & Liu, M. (2013). A heuristic method for two-stage hybrid flow shop with dedicated machines. 500 Computers & Operations Research, 40, 438–450. 501 Yokoyama, M. (2004). Scheduling for two-stage production system with setup and assembly operations. 502 Computers & Operations Research, 31, 2063–2078.
dc.rights.spa.fl_str_mv Atribución – No comercial – Compartir igual
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rights_invalid_str_mv Atribución – No comercial – Compartir igual
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spelling Ortiz Suarez, Miguel AngelBetancourt Ferrer, Leidy EsperanzaParra Negrete, Kevin ArmandoDe Felice, FabioPetrillo, Antonella2018-11-20T01:36:23Z2018-11-20T01:36:23Z2018-05-0102545330https://hdl.handle.net/11323/1383Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/In today highly competitive and globalized markets, an efficient use of production resources is necessary for manufacturing enterprises. In this research, the problem of scheduling and sequencing of manufacturing system is presented. A flexible job shop problem sequencing problem is analyzed in detail. After formulating this problem mathematically, a new model is proposed. This problem is not only theoretically interesting, but also practically relevant. An illustrative example is also conducted to demonstrate the applicability of the proposed model.Ortiz Suarez, Miguel Angel-0000-0001-6890-7547-600Betancourt Ferrer, Leidy Esperanza-7dc4bbcc-04ee-475b-8586-923da63be455-0Parra Negrete, Kevin Armando-0000-0003-0276-3215-600De Felice, Fabio-59da3a34-48d5-40ee-b35e-281128b3dd89-0Petrillo, Antonella-9aef617a-dab4-4777-bed1-d698823e08a6-0engAnnals Of Operations ResearchAtribución – No comercial – Compartir igualinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Flexible Job-Shop SystemOptimizationReconfigurable SystemSequencing ProblemDispatching algorithm for production programming of flexible job-shop systems in the smart factory industryArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersion430 Alvarez-Valdes, R., Fuertes, A., Tamarit, J. M., Giménez, G., & Ramos, R. (2005). A heuristic to schedule 431 flexible job-shop in a glass factory. European Journal of Operational Research, 165(2005), 525–534. 432 Baker, K. R. (2005). Elements of sequencing and scheduling. Hanover, NH: Tuck School of Business. 433 Barrios, M. A. O., Caballero, J. E., & Sánchez, F. S. (2015). A methodology for the creation of integrated service 434 networks in outpatient internal medicine. In Ambient intelligence for health (pp. 247–257). Springer. 435 Bozek, A., & Wysocki, M. (2015). Flexible job shop with continuous material flow. International Journal of 436 Production Research, 53(4), 1273–1290. 437 Brandimarte, P. (1993). Routing and scheduling in a flexible job shop by Tabu search. Annals of Operations 438 Research, 41(3), 157–183. 439 Calleja, G., & Pastor, R. (2014). A dispatching algorithm for flexible job-shop scheduling with transfer batches: 440 An industrial application. Production Planning & Control, 25(2), 93–109. 441 De Felice, F., & Petrillo, A. (2013). Simulation approach for the optimization of the layout in a manufacturing 442 firm. 24th IASTED international conference on modelling and simulation, MS 2013; Banff, AB; Canada; 443 17 July 2013 through 19 July 2013 (pp. 152–161). 444 Demir, Y., & I¸sleyen, S. K. (2014). An effective genetic algorithm for flexible job-shop scheduling with 445 overlapping in operations. International Journal of Production Research, 52(13), 3905–3921. 446 Digiesi, S., Mossa, G., & Mummolo, G. (2013). A sustainable order quantity model under uncertain product 447 demand. 7th IFAC conference on manufacturing modelling, management, and control, MIM 2013 (pp. 448 664–669). Saint Petersburg; Russian Federation; 19 June–21 June. 449 Fattahi, F., & Fallahi, A. (2010). Dynamic scheduling in flexible job shop systems by considering simultane450 ously efficiency and stability. CIRP Journal of Manufacturing Science and Technology, 2, 114–123. 451 Fattahi, P., Hosseini, S. M. H., Jolai, F., & Tavakkoli-Moghaddam, R. (2014). A branch and bound algorithm 452 for hybrid flow shop scheduling problem with setup time and assembly operations. Applied Mathematical 453 Modelling, 38, 119–134. 454 Gholami, O., & Sotskov, Y. N. (2014). Solving parallel machines job-shop scheduling problems by an adaptive 455 algorithm. International Journal of Production Research, 52(13), 3888–3904. 456 Guo, W. J. (2006). Algorithms for two-stage flexible flow shop scheduling with fuzzy processing times. NanJing: 457 NanJing University of Science & Technology. 458 Hassin, R., & Shani, M. (2005). Machine scheduling with earliness, tardiness and nonexecution penalties. 459 Computers & Operations Research, 32, 683–705. 460 Herazo-Padilla, N., Montoya-Torres, J. R., Isaza, S. N., & Alvarado-Valencia, J. (2015). Simulation461 optimization approach for the stochastic location-routing problem. Journal of Simulation, 9(4), 296–311. 462 Hildebrandt, T., Heger, J., & Scholz-Reiter, B. (2010). Towards improved dispatching rules for complex shop 463 floor scenarios—A genetic programming approach. GECCO’10, July 7–11, 2010. Portland, Oregon, 464 USA. 465 Hu, H. (2015). Adaptive scheduling model in hybrid flowshop production control using petri net. International 466 Journal of Control and Automation, 8(1), 233–242. 467 Jansen K, Mastrolilli M, & Solis-Oba R, (2000). Approximation algorithms for Flexible Job Shop Problems. 468 In: Lecture notes in computer science, Vol. 1776. Proceedings of the fourth Latin American symposium 469 on theoretical informatics (pp. 68–77). Berlin: Springer. 470 Jungwattanakit, J., Reodecha, M., Chaovalitwongse, P., & Werner, F. (2009). A comparison of scheduling 471 algorithms for flexible flow shop problems with unrelated parallel machines, setup times, and dual 472 criteria. Computers and Operations Research, 36(2), 358–378. 473 Kacem, I., Hammadi, S., & Borne, P. (2002). Pareto-optimality Approach for Flexible Job-shop Scheduling 474 Problems: Hybridization of Evolutionary Algorithms and Fuzzy Logic. Journal of Mathematics and 475 Computers in Simulation 476 Karimi-Nasab, M., & Modarres, M. (2015). Lot sizing and job shop scheduling with compressible process 477 times: A cut and branch approach. Computers & Industrial Engineering, 85, 196–205. 478 Kurz, M. E., & Askin, R. G. (2004). Scheduling flexible flow lines with sequence dependent setup times. 479 European Journal of Operational Research, 159(1), 66–82. 480 Logendran, R., Carson, S., & Hanson, E. (2005). Grouping scheduling in flexible flow shops. International 481 Journal of Production Economics, 96(2), 143–155. 482 Pezzella, F., Morganti, G., & Ciaschetti, G. (2008). A genetic algorithm for the Flexible Job-shop Scheduling 483 Problem. Computers & Operations Research, 35, 3202–3212. 484 Pinedo, M. (2001). Scheduling: Theory, algorithms, and systems. Upper Saddle River, NJ: Prentice Hall. 485 Prot, D., Bellenguez-Morineau, O., & Lahlou, C. (2013). New complexity results for parallel identical machine 486 scheduling problems with preemption, release dates and regular criteria. European Journal of Operational 487 Research, 231, 282–287. 488 Riane, F., Artiba, A., & Elmaghraby, S. E. (2002). Sequencing a hybrid two-stage flow shop with dedicated 489 machines. Int. J. Prod. Res., 40, 4353–4380. 490 Shen, X.-N., & Yao, X. (2015). Mathematical modeling and multi-objective evolutionary algorithms applied 491 to dynamic flexible job shop scheduling problems. Information Sciences, 298, 198–224. 492 Sotskov, Y. N., & Gholami, O. (2015). Mixed graph model and algorithms for parallel-machine job-shop 493 scheduling problems. International Journal of Production Research, 55(6), 1549–1564. 494 Sun, D.-H., He, W., Zheng, L.-J., & Liao, X.-Y. (2014). Scheduling flexible job shop problem subject to machine 495 breakdown with game theory. International Journal of Production Research, 52(13), 3858–3876. 496 Türkylmaz, A., & Bulkan, S. (2015). A hybrid algorithm for total tardiness minimization in flexible job shop: 497 Genetic algorithm with parallel VNS execution. International Journal of Production Research, 53(6), 498 1832–1848. 499 Wang, S., & Liu, M. (2013). A heuristic method for two-stage hybrid flow shop with dedicated machines. 500 Computers & Operations Research, 40, 438–450. 501 Yokoyama, M. (2004). Scheduling for two-stage production system with setup and assembly operations. 502 Computers & Operations Research, 31, 2063–2078.PublicationORIGINALDispatching Algorithm.pdfDispatching Algorithm.pdfapplication/pdf803083https://repositorio.cuc.edu.co/bitstreams/d633c018-a340-4082-8482-bc2f23dd86fd/download19878bea7e9714d1067274227e1e46b9MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.cuc.edu.co/bitstreams/2c8b4097-30a7-47b8-af7a-77801c3acc14/download8a4605be74aa9ea9d79846c1fba20a33MD52THUMBNAILDispatching Algorithm.pdf.jpgDispatching Algorithm.pdf.jpgimage/jpeg30213https://repositorio.cuc.edu.co/bitstreams/a40d7355-aa1f-46aa-aba8-d9ab2e905c4f/downloadad36e32b7fd4084c5f0b975eb4c08db4MD54TEXTDispatching Algorithm.pdf.txtDispatching Algorithm.pdf.txttext/plain57997https://repositorio.cuc.edu.co/bitstreams/4cb40e74-f210-4268-ae58-e1c79e09f834/download842a33bfd570b31b074a7a45dcb8d392MD5511323/1383oai:repositorio.cuc.edu.co:11323/13832024-09-17 14:05:06.27open.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa CUCrepdigital@cuc.edu.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