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Ergonomic risk and cycle time minimization for the U-shaped worker assignment assembly line balancing problem: A multi-objective approach

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Ergonomic risk and cycle time minimization for the U-shaped worker assignment assembly line balancing problem: A multi-objective approach

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Zhang, Z.; Tang, Q.; Ruiz García, R.; Zhang, L. (2020). Ergonomic risk and cycle time minimization for the U-shaped worker assignment assembly line balancing problem: A multi-objective approach. Computers & Operations Research. 118:1-15. https://doi.org/10.1016/j.cor.2020.104905

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Título: Ergonomic risk and cycle time minimization for the U-shaped worker assignment assembly line balancing problem: A multi-objective approach
Autor: Zhang, Zikai Tang, QiuHua Ruiz García, Rubén Zhang, Liping
Entidad UPV: Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat
Fecha difusión:
Resumen:
[EN] Workers still perform the bulk of operations in the manufacturing industry. The consideration of the assignment of workers and the reduction of ergonomic risks in U-shaped assembly lines is of paramount importance. ...[+]
Palabras clave: U-shaped assembly line , Worker assignment , Ergonomic risks , Multi-objectives
Derechos de uso: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
Fuente:
Computers & Operations Research. (issn: 0305-0548 )
DOI: 10.1016/j.cor.2020.104905
Editorial:
Elsevier
Versión del editor: https://doi.org/10.1016/j.cor.2020.104905
Código del Proyecto:
info:eu-repo/grantAgreement/NSFC//51875420/
info:eu-repo/grantAgreement/NSFC//51875421/
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/
Agradecimientos:
The authors would like to thank the anonymous reviewers for their helpful comments and constructive suggestions. This work is supported by National Natural Science Foundation of China (No. 51875421, No. 51875420). Ruben ...[+]
Tipo: Artículo

References

Akyol, S. D., & Baykasoğlu, A. (2016). A multiple-rule based constructive randomized search algorithm for solving assembly line worker assignment and balancing problem. Journal of Intelligent Manufacturing, 30(2), 557-573. doi:10.1007/s10845-016-1262-6

Akyol, S. D., & Baykasoğlu, A. (2016). ErgoALWABP: a multiple-rule based constructive randomized search algorithm for solving assembly line worker assignment and balancing problem under ergonomic risk factors. Journal of Intelligent Manufacturing, 30(1), 291-302. doi:10.1007/s10845-016-1246-6

Alavidoost, M. H., Babazadeh, H., & Sayyari, S. T. (2016). An interactive fuzzy programming approach for bi-objective straight and U-shaped assembly line balancing problem. Applied Soft Computing, 40, 221-235. doi:10.1016/j.asoc.2015.11.025 [+]
Akyol, S. D., & Baykasoğlu, A. (2016). A multiple-rule based constructive randomized search algorithm for solving assembly line worker assignment and balancing problem. Journal of Intelligent Manufacturing, 30(2), 557-573. doi:10.1007/s10845-016-1262-6

Akyol, S. D., & Baykasoğlu, A. (2016). ErgoALWABP: a multiple-rule based constructive randomized search algorithm for solving assembly line worker assignment and balancing problem under ergonomic risk factors. Journal of Intelligent Manufacturing, 30(1), 291-302. doi:10.1007/s10845-016-1246-6

Alavidoost, M. H., Babazadeh, H., & Sayyari, S. T. (2016). An interactive fuzzy programming approach for bi-objective straight and U-shaped assembly line balancing problem. Applied Soft Computing, 40, 221-235. doi:10.1016/j.asoc.2015.11.025

Alavidoost, M. H., Tarimoradi, M., & Zarandi, M. H. F. (2015). Fuzzy adaptive genetic algorithm for multi-objective assembly line balancing problems. Applied Soft Computing, 34, 655-677. doi:10.1016/j.asoc.2015.06.001

Araújo, F. F. B., Costa, A. M., & Miralles, C. (2012). Two extensions for the ALWABP: Parallel stations and collaborative approach. International Journal of Production Economics, 140(1), 483-495. doi:10.1016/j.ijpe.2012.06.032

Aryanezhad, M. B., Kheirkhah, A. S., Deljoo, V., & Mirzapour Al-e-hashem, S. M. J. (2008). Designing safe job rotation schedules based upon workers’ skills. The International Journal of Advanced Manufacturing Technology, 41(1-2), 193-199. doi:10.1007/s00170-008-1446-0

Avikal, S., Jain, R., Mishra, P. K., & Yadav, H. C. (2013). A heuristic approach for U-shaped assembly line balancing to improve labor productivity. Computers & Industrial Engineering, 64(4), 895-901. doi:10.1016/j.cie.2013.01.001

Battini, D., Calzavara, M., Otto, A., & Sgarbossa, F. (2016). The Integrated Assembly Line Balancing and Parts Feeding Problem with Ergonomics Considerations. IFAC-PapersOnLine, 49(12), 191-196. doi:10.1016/j.ifacol.2016.07.594

Battini, D., Faccio, M., Persona, A., & Sgarbossa, F. (2011). New methodological framework to improve productivity and ergonomics in assembly system design. International Journal of Industrial Ergonomics, 41(1), 30-42. doi:10.1016/j.ergon.2010.12.001

Bautista, J., Batalla-García, C., & Alfaro-Pozo, R. (2016). Models for assembly line balancing by temporal, spatial and ergonomic risk attributes. European Journal of Operational Research, 251(3), 814-829. doi:10.1016/j.ejor.2015.12.042

Baykasoglu, A. (2006). Multi-rule Multi-objective Simulated Annealing Algorithm for Straight and U Type Assembly Line Balancing Problems. Journal of Intelligent Manufacturing, 17(2), 217-232. doi:10.1007/s10845-005-6638-y

Baykasoğlu, A., Demirkol Akyol, S., & Demirkan, B. (2017). An Excel-based program to teach students quick ergonomic risk assessment techniques with an application to an assembly system. Computer Applications in Engineering Education, 25(3), 489-507. doi:10.1002/cae.21816

Baykasoglu, A., Tasan, S. O., Tasan, A. S., & Akyol, S. D. (2017). Modeling and solving assembly line design problems by considering human factors with a real-life application. Human Factors and Ergonomics in Manufacturing & Service Industries, 27(2), 96-115. doi:10.1002/hfm.20695

Blum, C., & Miralles, C. (2011). On solving the assembly line worker assignment and balancing problem via beam search. Computers & Operations Research, 38(1), 328-339. doi:10.1016/j.cor.2010.05.008

Borba, L., & Ritt, M. (2014). A heuristic and a branch-and-bound algorithm for the Assembly Line Worker Assignment and Balancing Problem. Computers & Operations Research, 45, 87-96. doi:10.1016/j.cor.2013.12.002

Bortolini, M., Faccio, M., Gamberi, M., & Pilati, F. (2017). Multi-objective assembly line balancing considering component picking and ergonomic risk. Computers & Industrial Engineering, 112, 348-367. doi:10.1016/j.cie.2017.08.029

Botti, L., Mora, C., & Regattieri, A. (2017). Integrating ergonomics and lean manufacturing principles in a hybrid assembly line. Computers & Industrial Engineering, 111, 481-491. doi:10.1016/j.cie.2017.05.011

Bukchin, Y., & Raviv, T. (2018). Constraint programming for solving various assembly line balancing problems. Omega, 78, 57-68. doi:10.1016/j.omega.2017.06.008

Costa, A. M., & Miralles, C. (2009). Job rotation in assembly lines employing disabled workers. International Journal of Production Economics, 120(2), 625-632. doi:10.1016/j.ijpe.2009.04.013

Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), 182-197. doi:10.1109/4235.996017

Ding, J.-Y., Song, S., Gupta, J. N. D., Zhang, R., Chiong, R., & Wu, C. (2015). An improved iterated greedy algorithm with a Tabu-based reconstruction strategy for the no-wait flowshop scheduling problem. Applied Soft Computing, 30, 604-613. doi:10.1016/j.asoc.2015.02.006

Fattahi, A., Elaoud, S., Sadeqi Azer, E., & Turkay, M. (2013). A novel integer programming formulation with logic cuts for the U-shaped assembly line balancing problem. International Journal of Production Research, 52(5), 1318-1333. doi:10.1080/00207543.2013.832489

Grunert da Fonseca, V., Fonseca, C.M., Hall, A.O., 2001. Inferential performance assessment of stochastic optimisers and the attainment function. 1993, 213–225.

Guo, Z. X., Wong, W. K., Leung, S. Y. S., Fan, J. T., & Chan, S. F. (2008). A Genetic-Algorithm-Based Optimization Model for Solving the Flexible Assembly Line Balancing Problem With Work Sharing and Workstation Revisiting. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 38(2), 218-228. doi:10.1109/tsmcc.2007.913912

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

Hazır, Ö., & Dolgui, A. (2015). A decomposition based solution algorithm for U-type assembly line balancing with interval data. Computers & Operations Research, 59, 126-131. doi:10.1016/j.cor.2015.01.010

Hignett, S., & McAtamney, L. (2000). Rapid Entire Body Assessment (REBA). Applied Ergonomics, 31(2), 201-205. doi:10.1016/s0003-6870(99)00039-3

HOFFMANN, T. R. (1990). Assembly line balancing: a set of challenging problems. International Journal of Production Research, 28(10), 1807-1815. doi:10.1080/00207549008942835

Karhu, O., Kansi, P., & Kuorinka, I. (1977). Correcting working postures in industry: A practical method for analysis. Applied Ergonomics, 8(4), 199-201. doi:10.1016/0003-6870(77)90164-8

Knowles, J.D., Thiele, L., Zitzler, E., 2006. A tutorial on the performance assessment of stochastic multiobjective optimizers. TIK-Report 214.

López-Ibáñez, M., Paquete, L., & Stützle, T. (2006). Hybrid Population-Based Algorithms for the Bi-Objective Quadratic Assignment Problem. Journal of Mathematical Modelling and Algorithms, 5(1), 111-137. doi:10.1007/s10852-005-9034-x

Li, M., Tang, Q., Zheng, Q., Xia, X., & Floudas, C. A. (2017). Rules-based heuristic approach for the U-shaped assembly line balancing problem. Applied Mathematical Modelling, 48, 423-439. doi:10.1016/j.apm.2016.12.031

Li, Z., Tang, Q., & Zhang, L. (2017). Two-sided assembly line balancing problem of type I: Improvements, a simple algorithm and a comprehensive study. Computers & Operations Research, 79, 78-93. doi:10.1016/j.cor.2016.10.006

Liles, D. H., Deivanayagam, S., Ayoub, M. M., & Mahajan, P. (1984). A Job Severity Index for the Evaluation and Control of Lifting Injury. Human Factors: The Journal of the Human Factors and Ergonomics Society, 26(6), 683-693. doi:10.1177/001872088402600608

McAtamney, L., & Nigel Corlett, E. (1993). RULA: a survey method for the investigation of work-related upper limb disorders. Applied Ergonomics, 24(2), 91-99. doi:10.1016/0003-6870(93)90080-s

Miltenburg, G. J., & Wijngaard, J. (1994). The U-line Line Balancing Problem. Management Science, 40(10), 1378-1388. doi:10.1287/mnsc.40.10.1378

Minella, G., Ruiz, R., & Ciavotta, M. (2011). Restarted Iterated Pareto Greedy algorithm for multi-objective flowshop scheduling problems. Computers & Operations Research, 38(11), 1521-1533. doi:10.1016/j.cor.2011.01.010

Miralles, C., García-Sabater, J. P., Andrés, C., & Cardós, M. (2008). Branch and bound procedures for solving the Assembly Line Worker Assignment and Balancing Problem: Application to Sheltered Work centres for Disabled. Discrete Applied Mathematics, 156(3), 352-367. doi:10.1016/j.dam.2005.12.012

Moreira, M. C. O., Miralles, C., & Costa, A. M. (2015). Model and heuristics for the Assembly Line Worker Integration and Balancing Problem. Computers & Operations Research, 54, 64-73. doi:10.1016/j.cor.2014.08.021

Mutlu, Ö., Polat, O., & Supciller, A. A. (2013). An iterative genetic algorithm for the assembly line worker assignment and balancing problem of type-II. Computers & Operations Research, 40(1), 418-426. doi:10.1016/j.cor.2012.07.010

Nourmohammadi, A., Zandieh, M., & Tavakkoli-Moghaddam, R. (2013). An imperialist competitive algorithm for multi-objective U-type assembly line design. Journal of Computational Science, 4(5), 393-400. doi:10.1016/j.jocs.2012.09.001

OCCHIPINTI, E. (1998). OCRA: a concise index for the assessment of exposure to repetitive movements of the upper limbs. Ergonomics, 41(9), 1290-1311. doi:10.1080/001401398186315

Oksuz, M. K., Buyukozkan, K., & Satoglu, S. I. (2017). U-shaped assembly line worker assignment and balancing problem: A mathematical model and two meta-heuristics. Computers & Industrial Engineering, 112, 246-263. doi:10.1016/j.cie.2017.08.030

Otto, A., & Battaïa, O. (2017). Reducing physical ergonomic risks at assembly lines by line balancing and job rotation: A survey. Computers & Industrial Engineering, 111, 467-480. doi:10.1016/j.cie.2017.04.011

Otto, A., & Scholl, A. (2011). Incorporating ergonomic risks into assembly line balancing. European Journal of Operational Research, 212(2), 277-286. doi:10.1016/j.ejor.2011.01.056

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

Pereira, J. (2018). The robust (minmax regret) assembly line worker assignment and balancing problem. Computers & Operations Research, 93, 27-40. doi:10.1016/j.cor.2018.01.009

Polat, O., Kalayci, C. B., Mutlu, Ö., & Gupta, S. M. (2015). A two-phase variable neighbourhood search algorithm for assembly line worker assignment and balancing problem type-II: an industrial case study. International Journal of Production Research, 54(3), 722-741. doi:10.1080/00207543.2015.1055344

Rabbani, M., Kazemi, S. M., & Manavizadeh, N. (2012). Mixed model U-line balancing type-1 problem: A new approach. Journal of Manufacturing Systems, 31(2), 131-138. doi:10.1016/j.jmsy.2012.02.002

Ramezanian, R., & Ezzatpanah, A. (2015). Modeling and solving multi-objective mixed-model assembly line balancing and worker assignment problem. Computers & Industrial Engineering, 87, 74-80. doi:10.1016/j.cie.2015.04.017

Ritt, M., Costa, A. M., & Miralles, C. (2015). The assembly line worker assignment and balancing problem with stochastic worker availability. International Journal of Production Research, 54(3), 907-922. doi:10.1080/00207543.2015.1108534

Şahin, M., & Kellegöz, T. (2017). An efficient grouping genetic algorithm for U-shaped assembly line balancing problems with maximizing production rate. Memetic Computing, 9(3), 213-229. doi:10.1007/s12293-017-0239-0

Schaub, K., Caragnano, G., Britzke, B., & Bruder, R. (2013). The European Assembly Worksheet. Theoretical Issues in Ergonomics Science, 14(6), 616-639. doi:10.1080/1463922x.2012.678283

Shin, W., & Park, M. (2017). Ergonomic interventions for prevention of work-related musculoskeletal disorders in a small manufacturing assembly line. International Journal of Occupational Safety and Ergonomics, 25(1), 110-122. doi:10.1080/10803548.2017.1373487

Sungur, B., & Yavuz, Y. (2015). Assembly line balancing with hierarchical worker assignment. Journal of Manufacturing Systems, 37, 290-298. doi:10.1016/j.jmsy.2014.08.004

Talbot, F. B., Patterson, J. H., & Gehrlein, W. V. (1986). A Comparative Evaluation of Heuristic Line Balancing Techniques. Management Science, 32(4), 430-454. doi:10.1287/mnsc.32.4.430

Tan, K. C., Yang, Y. J., & Goh, C. K. (2006). A distributed Cooperative coevolutionary algorithm for multiobjective optimization. IEEE Transactions on Evolutionary Computation, 10(5), 527-549. doi:10.1109/tevc.2005.860762

Tasgetiren, M. F., Kizilay, D., Pan, Q.-K., & Suganthan, P. N. (2017). Iterated greedy algorithms for the blocking flowshop scheduling problem with makespan criterion. Computers & Operations Research, 77, 111-126. doi:10.1016/j.cor.2016.07.002

Tiacci, L., & Mimmi, M. (2018). Integrating ergonomic risks evaluation through OCRA index and balancing/sequencing decisions for mixed model stochastic asynchronous assembly lines. Omega, 78, 112-138. doi:10.1016/j.omega.2017.08.011

Vilà, M., & Pereira, J. (2014). A branch-and-bound algorithm for assembly line worker assignment and balancing problems. Computers & Operations Research, 44, 105-114. doi:10.1016/j.cor.2013.10.016

WATERS, T. R., PUTZ-ANDERSON, V., GARG, A., & FINE, L. J. (1993). Revised NIOSH equation for the design and evaluation of manual lifting tasks. Ergonomics, 36(7), 749-776. doi:10.1080/00140139308967940

Yorke, J., 2017. Henry Ford – Master of flow.

Zacharia, P. T., & Nearchou, A. C. (2016). A population-based algorithm for the bi-objective assembly line worker assignment and balancing problem. Engineering Applications of Artificial Intelligence, 49, 1-9. doi:10.1016/j.engappai.2015.11.007

Zaman, T., Paul, S. K., & Azeem, A. (2012). Sustainable operator assignment in an assembly line using genetic algorithm. International Journal of Production Research, 50(18), 5077-5084. doi:10.1080/00207543.2011.636764

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