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Journals / Endüstri Mühendisliği / 2026 / Cilt: 37 Sayı: 2

MULTI-CHOICE CONIC GOAL PROGRAMMING MODEL FOR ASSEMBLY LINE BALANCING PROBLEM WITH SEQUENCE DEPENDENT SETUP TIME AND WORKER DEPENDENT PROCESSING TIME

SIRA BAĞIMLI HAZIRLIK SÜRELİ VE İŞÇİ BAĞIMLI İŞLEM SÜRELİ MONTAJ HATTI DENGELEME PROBLEMİ İÇİN ÇOK SEÇENEKLİ KONİK HEDEF PROGRAMLAMA MODELİ

Dilara Menkis(ESKİŞEHİR OSMANGAZİ ÜNİVERSİTESİ, MÜHENDİSLİK-MİMARLIK FAKÜLTESİ, ENDÜSTRİ MÜHENDİSLİĞİ BÖLÜMÜ, ENDÜSTRİ MÜHENDİSLİĞİ PR.)0009-0003-0081-3730
Tuğba Saraç(ESKİŞEHİR OSMANGAZİ ÜNİVERSİTESİ, MÜHENDİSLİK-MİMARLIK FAKÜLTESİ, ENDÜSTRİ MÜHENDİSLİĞİ BÖLÜMÜ)0000-0002-8115-3206
Pages
293–329
Publication Date
2026-08-28
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

This way, workers are given time to solve problems that may be encountered during material supply and process.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study deals with bi-objective optimization of an assembly line balancing problem where straight-line layout and single model are produced.
📊
Key Findings & Data:In this problem, since workers have different performances, processing times may vary depending on the worker assigned to that job and setup times are sequence dependent.
💡
Conclusion & Impact:This way, workers are given time to solve problems that may be encountered during material supply and process.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Montaj hattı dengeleme · Çok seçenekli konik hedef programlama · Sıra bağımlı hazırlık süreleri

Abstract

This study deals with bi-objective optimization of an assembly line balancing problem where straight-line layout and single model are produced. Objective functions are minimization of cycle time and completion time. In this problem, since workers have different performances, processing times may vary depending on the worker assigned to that job and setup times are sequence dependent. A mathematical model is developed for the considered problem. Multi-choice conic goal programming method is used to solve the proposed bi-objective model. Test problems taken from the literature are used to demonstrate the performance of the proposed solution approach. The obtained results are compared with the results of the classical goal programming method. Non-dominated solutions that cannot be obtained with classical goal programming are reached. By considering worker-dependent processing times and sequence-dependent setup times, improvements are provided in cycle time and completion time. This way, workers are given time to solve problems that may be encountered during material supply and process.

Özet

Bu çalışma, düz hat düzeni ve tek modelin üretildiği bir montaj hattı dengeleme probleminin iki amaçlı optimizasyonunu ele almaktadır. Bu amaçlar çevrim süresinin ve tamamlanma zamanının enküçüklenmesidir. Ele alınan problemde, işçiler farklı performansa sahip olduklarından işlem süreleri, o işe atanan işçiye bağlı olarak değişebilmektedir ve hazırlık süreleri sıra bağımlıdır. Ele alınan problem için bir matematiksel model geliştirilmiştir. Önerilen iki amaçlı modelin çözümü için çok seçenekli konik hedef programlama yöntemi kullanılmıştır. Önerilen çözüm yaklaşımının performansını gösterebilmek için literatürden alınan test problemleri kullanılmıştır. Elde edilen sonuçlar, klasik hedef programlama yönteminin sonuçları ile kıyaslanmıştır. Klasik hedef programlama ile elde edilemeyen baskın çözümlere ulaşılmıştır. İşçi bağımlı işlem sürelerinin ve sıra bağımlı hazırlık sürelerinin dikkate alınmasıyla çevrim süresi ve tamamlanma zamanında iyileşmeler sağlanmıştır. Bu sayede işçilere malzeme tedariği ve işlem esnasında karşılaşılabilecekleri problemleri çözebilmeleri için zaman kazandırılmıştır.

🔖

Cite This Article

Menkis, D., Saraç, T. (2026). MULTI-CHOICE CONIC GOAL PROGRAMMING MODEL FOR ASSEMBLY LINE BALANCING PROBLEM WITH SEQUENCE DEPENDENT SETUP TIME AND WORKER DEPENDENT PROCESSING TIME. Endüstri Mühendisliği, Cilt: 37 Sayı: 2, 293–329. https://doi.org/10.46465/endustrimuhendisligi.1782444

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References (76)

  1. Akpınar, S., Bayhan, G. M. ve Baykasoglu, A. (2013). Hybridizing ant colony optimization via genetic algorithm for mixed-model assembly line balancing problem with sequence dependent setup times between tasks. Applied Soft Computing, 13(1), 574-589. Doi: https://doi.org/10.1016/ j.asoc.2012.07.024
  2. Akpinar, Ş. ve Baykasoğlu, A. (2014a). Modeling and solving mixed-model assembly line balancing problem with setups. Part I: A mixed integer linear programming model. Journal of manufacturing systems, 33(1), 177-187. Doi: https://doi.org/10.1016/j.jmsy.2013.11.004
  3. Akpinar, Ş. ve Baykasoğlu, A. (2014b). Modeling and solving mixed-model assembly line balancing problem with setups. Part II: A multiple colony hybrid bees algorithm. Journal of Manufacturing Systems, 33(4), 445-461. Doi: https://doi.org/10.1016/j.jmsy.2014.04.001
  4. Akpinar, S. Elmi, A., ve Bektaş, T. (2017). Combinatorial Benders cuts for assembly line balancing problems with setups. European Journal of Operational Research, 259(2), 527-537. Doi: https://doi.org/10.1016/ j.ejor.2016.11.001
  5. Andrés, C., Miralles, C. ve Pastor, R. (2008). Balancing and scheduling tasks in assembly lines with sequence-dependent setup times. European Journal of Operational Research, 187(3), 1212-1223. Doi: https://doi.org/10.1016/ j.ejor.2006.07.044
  6. Aslan, Ş. (2023). Mathematical model and a variable neighborhood search algorithm for mixed-model robotic two-sided assembly line balancing problems with sequence-dependent setup times. Optimization and Engineering, 24(2), 989-1016. Doi: https://doi.org/10.1007/s11081-022-09718-3
  7. Babazadeh, H. ve Javadian, N. (2019). A novel meta-heuristic approach to solve fuzzy multi-objective straight and U-shaped assembly line balancing problems. Soft Computing, 23(17), 8217-8245. Doi: https://doi.org/ 10.1007/s00500-018-3457-6
  8. Battaïa, O. ve Dolgui, A. (2022). Hybridizations in line balancing problems: A comprehensive review on new trends and formulations. International Journal of Production Economics, 250, 108673. Doi: https://doi.org/ 10.1016/j.ijpe.2022.108673
  9. Becker, C. ve Scholl, A. (2006). A survey on problems and methods in generalized assembly line balancing. European journal of operational research, 168(3), 694-715. Doi: https://doi.org/10.1016/j.ejor.2004.07.023
  10. Boysen, N., Schulze, P. ve Scholl, A. (2022). Assembly line balancing: What happened in the last fifteen years?. European Journal of Operational Research, 301(3), 797-814. Doi: https://doi.org/10.1016/j.ejor.2021.11.043 Chang, C. T. (2007). Multi-choice goal programming. Omega, 35(4), 389-396. Doi: https://doi.org/10.1016/j.omega.2005.07.009
  11. Didden, J. B., Lefeber, E., Adan, I. J. ve Panhuijzen, I. W. F. (2023). Genetic algorithm and decision support for assembly line balancing in the automotive industry. International Journal of Production Research, 61(10), 3377-3395. Doi: https://doi.org/10.1080/00207543.2022.2081630
  12. Diri, Z., Mete, S., Çil, Z. A. ve Ağpak, K. (2015). Stokastik Sıra-Bağımlı Hazırlık Zamanlı Montaj Hattı Dengeleme Problemi. Pamukkale University Journal of Engineering Sciences, 21(4). Doi: https://doi.org/10.5505/pajes.2015.93723
  13. Güner, F., Görür, A. K., Satır, B., Kandiller, L. ve Drake, J. H. (2024). A constraint programming approach to a real-world workforce scheduling problem for multi-manned assembly lines with sequence-dependent setup times. International Journal of Production Research, 62(9), 3212-3229. Doi: https://doi.org/10.1080/00207543.2023.2226772
  14. Hamta, N., Ghomi, S. F., Jolai, F. ve Shirazi, M. A. (2013). A hybrid PSO algorithm for a multi-objective assembly line balancing problem with flexible operation times, sequence-dependent setup times and learning effect. International Journal of Production Economics, 141(1), 99-111. Doi: https://doi.org/10.1016/j.ijpe.2012.03.013
  15. Huang, Y., Sheng, B., Fu, G., Luo, R. ve Lu, Y. (2024). Multi-objective simulated annealing algorithm for robotic mixed-model two-sided assembly line balancing with setup times and multiple constraints. Applied Soft Computing, 156, 111507. Doi: https://doi.org/10.1016/j.asoc.2024.111507
  16. Janardhanan, M. N., Li, Z., Bocewicz, G., Banaszak, Z. ve Nielsen, P. (2019). Metaheuristic algorithms for balancing robotic assembly lines with sequence-dependent robot setup times. Applied Mathematical Modelling, 65, 256-270. Doi: https://doi.org/10.1016/j.apm.2018.08.016
  17. Khorram, M., Eghtesadifard, M. ve Niroomand, S. (2022). Hybrid meta-heuristic algorithms for U-shaped assembly line balancing problem with equipment and worker allocations. Soft Computing, 26(5), 2241-2258. Doi: https://doi.org/10.1007/s00500-021-06472-z
  18. Kılınçcı, Ö. (2023). Kaynak ve sıra bağımlı hazırlık süreli montaj hattı dengeleme problemi (KHMHDP). Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 38(1), 557-570. Doi: https://doi.org/10.17341/gazimmfd.757276
  19. Lahrichi, Y., Damand, D., Deroussi, L., Grangeon, N. ve Norre, S. (2023). Investigating two variants of the sequence-dependent robotic assembly line balancing problem by means of a split-based approach. International Journal of Production Research, 61(7), 2322-2338. Doi: https://doi.org/ 10.1080/00207543.2022.2062266
  20. Lee, A. H., Kang, H. Y. ve Chen, C. L. (2021). Multi-objective assembly line balancing problem with setup times using fuzzy goal programming and genetic algorithm. Symmetry, 13(2), 333. Doi: https://doi.org/ 10.3390/sym13020333
  21. Li, Z., Janardhanan, M. N., Tang, Q. ve Ponnambalam, S. G. (2019). Model and metaheuristics for robotic two-sided assembly line balancing problems with setup times. Swarm and Evolutionary Computation, 50, 100567. Doi: https://doi.org/10.1016/j.swevo.2019.100567
  22. Li, Z., Janardhanan, M. N. ve Ponnambalam, S. G. (2021). Cost-oriented robotic assembly line balancing problem with setup times: multi-objective algorithms. Journal of Intelligent Manufacturing, 32, 989-1007. Doi: https://doi.org/10.1007/s10845-020-01598-7
  23. Li, Z., Sikora, C. G. S. ve Kucukkoc, I. (2024). Chance-constrained stochastic assembly line balancing with branch, bound and remember algorithm. Annals of Operations Research, 335(1), 491-516. Doi: https://doi.org/ 10.1007/s10479-023-05809-1
  24. Martino, L. ve Pastor, R. (2010). Heuristic procedures for solving the general assembly line balancing problem with setups. International Journal of Production Research, 48(6), 1787-1804. Doi: https://doi.org/ 10.1080/00207540802577979
  25. Özcan, U. ve Toklu, B. (2010). Balancing two-sided assembly lines with sequence-dependent setup times. International Journal of Production Research, 48(18), 5363-5383. Doi: https://doi.org/10.1080/00207540903140750
  26. Özcan, U. (2019). Balancing and scheduling tasks in parallel assembly lines with sequence-dependent setup times. International Journal of Production Economics, 213, 81-96. Doi: https://doi.org/10.1016/j.ijpe.2019.02.023
  27. Rabbani, M., Mousavi, Z. ve Farrokhi-Asl, H. (2016a). Multi-objective metaheuristics for solving a type II robotic mixed-model assembly line balancing problem. Journal of Industrial and Production Engineering, 33(7), 472-484. Doi: https://doi.org/10.1080/21681015.2015.1126656
  28. Rabbani, M., Siadatian, R., Farrokhi-Asl, H. ve Manavizadeh, N. (2016b). Multi-objective optimization algorithms for mixed model assembly line balancing problem with parallel workstations. Cogent Engineering, 3(1), 1158903. Doi: https://doi.org/10.1080/23311916.2016.1158903
  29. Rabbani, M., Alipour, F., Farrokhi-Asl, H. ve Manavizadeh, N. (2018). Using metaheuristic algorithms for solving a mixed model assembly line balancing problem considering express parallel line and learning effect. Brazilian Journal of Operations & Production Management, 15(2), 254-269. Doi: https://doi.org/10.14488/BJOPM.2018.v15.n2.a8
  30. Samouei, P. ve Sobhishoja, M. (2023). Robust counterpart mathematical models for balancing, sequencing, and assignment of robotic U-shaped assembly lines with considering failures and setup times. OPSEARCH, 60(1), 87-124. Doi: https://doi.org/10.1007/s12597-022-00609-w
  31. Seyed-Alagheband, S. A., Ghomi, S. F. ve Zandieh, M. (2011). A simulated annealing algorithm for balancing the assembly line type II problem with sequence-dependent setup times between tasks. International Journal of Production Research, 49(3), 805-825. Doi: https://doi.org/10.1080/ 00207540903471486
  32. Scholl, A., Boysen, N. ve Fliedner, M. (2013). The assembly line balancing and scheduling problem with sequence-dependent setup times: problem extension, model formulation and efficient heuristics. OR spectrum, 35, 291-320. Doi: https://doi.org/10.1007/s00291-011-0265-0
  33. Sivasankaran, P. ve Shahabudeen, P. (2014). Literature review of assembly line balancing problems. The International Journal of Advanced Manufacturing Technology, 73, 1665-1694. Doi: https://doi.org/10.1007/s00170-014-5944-y
  34. Ustun, O. (2012). Multi-choice goal programming formulation based on the conic scalarizing function. Applied Mathematical Modelling, 36(3), 974-988. Doi: https://doi.org/10.1016/j.apm.2011.07.065
  35. Yang, W. ve Cheng, W. (2020a). A Mathematical Model and a Simulated Annealing Algorithm for Balancing Multi‐manned Assembly Line Problem with Sequence‐Dependent Setup Time. Mathematical problems in Engineering, 2020(1), 8510253. Doi: https://doi.org/10.1155/2020/8510253
  36. Yang, W. ve Cheng, W. (2020b). Modelling and solving mixed-model two-sided assembly line balancing problem with sequence-dependent setup time. International Journal of Production Research, 58(21), 6638-6659. Doi: https://doi.org/10.1080/00207543.2019.1683255
  37. Yilmaz, H. (2021). Modeling and solving assembly line worker assignment and balancing problem with sequence-dependent setup times.Soft Computing, 25(20), 12899-12914. Doi: https://doi.org/10.1007/s00500-021-06107-3
  38. Yolmeh, A. ve Kianfar, F. (2012). An efficient hybrid genetic algorithm to solve assembly line balancing problem with sequence-dependent setup times. Computers & industrial engineering, 62(4), 936-945. Doi: https://doi.org/10.1016/j.cie.2011.12.017
  39. Yoosefelahi, A., Aminnayeri, M., Mosadegh, H. ve Ardakani, H. D. (2012). Type II robotic assembly line balancing problem: An evolution strategies algorithm for a multi-objective model. Journal of Manufacturing Systems, 31(2), 139-151. Doi: https://doi.org/10.1016/j.jmsy.2011.10.002
  40. Akpınar, S., Bayhan, G. M. ve Baykasoglu, A. (2013). Hybridizing ant colony optimization via genetic algorithm for mixed-model assembly line balancing problem with sequence dependent setup times between tasks. Applied Soft Computing, 13(1), 574-589. Doi: https://doi.org/10.1016/ j.asoc.2012.07.024
  41. Akpinar, Ş. ve Baykasoğlu, A. (2014a). Modeling and solving mixed-model assembly line balancing problem with setups. Part I: A mixed integer linear programming model. Journal of manufacturing systems, 33(1), 177-187. Doi: https://doi.org/10.1016/j.jmsy.2013.11.004
  42. Akpinar, Ş. ve Baykasoğlu, A. (2014b). Modeling and solving mixed-model assembly line balancing problem with setups. Part II: A multiple colony hybrid bees algorithm. Journal of Manufacturing Systems, 33(4), 445-461. Doi: https://doi.org/10.1016/j.jmsy.2014.04.001
  43. Aslan, Ş. (2023). Mathematical model and a variable neighborhood search algorithm for mixed-model robotic two-sided assembly line balancing problems with sequence-dependent setup times. Optimization and Engineering, 24(2), 989-1016. Doi: https://doi.org/10.1007/s11081-022-09718-3
  44. Babazadeh, H. ve Javadian, N. (2019). A novel meta-heuristic approach to solve fuzzy multi-objective straight and U-shaped assembly line balancing problems. Soft Computing, 23(17), 8217-8245. Doi: https://doi.org/ 10.1007/s00500-018-3457-6
  45. Battaïa, O. ve Dolgui, A. (2022). Hybridizations in line balancing problems: A comprehensive review on new trends and formulations. International Journal of Production Economics, 250, 108673. Doi: https://doi.org/ 10.1016/j.ijpe.2022.108673
  46. Becker, C. ve Scholl, A. (2006). A survey on problems and methods in generalized assembly line balancing. European journal of operational research, 168(3), 694-715. Doi: https://doi.org/10.1016/j.ejor.2004.07.023
  47. Boysen, N., Schulze, P. ve Scholl, A. (2022). Assembly line balancing: What happened in the last fifteen years?. European Journal of Operational Research, 301(3), 797-814. Doi: https://doi.org/10.1016/j.ejor.2021.11.043 Chang, C. T. (2007). Multi-choice goal programming. Omega, 35(4), 389-396. Doi: https://doi.org/10.1016/j.omega.2005.07.009
  48. Didden, J. B., Lefeber, E., Adan, I. J. ve Panhuijzen, I. W. F. (2023). Genetic algorithm and decision support for assembly line balancing in the automotive industry. International Journal of Production Research, 61(10), 3377-3395. Doi: https://doi.org/10.1080/00207543.2022.2081630
  49. Diri, Z., Mete, S., Çil, Z. A. ve Ağpak, K. (2015). Stokastik Sıra-Bağımlı Hazırlık Zamanlı Montaj Hattı Dengeleme Problemi. Pamukkale University Journal of Engineering Sciences, 21(4). Doi: https://doi.org/10.5505/pajes.2015.93723
  50. Güner, F., Görür, A. K., Satır, B., Kandiller, L. ve Drake, J. H. (2024). A constraint programming approach to a real-world workforce scheduling problem for multi-manned assembly lines with sequence-dependent setup times. International Journal of Production Research, 62(9), 3212-3229. Doi: https://doi.org/10.1080/00207543.2023.2226772
  51. Hamta, N., Ghomi, S. F., Jolai, F. ve Shirazi, M. A. (2013). A hybrid PSO algorithm for a multi-objective assembly line balancing problem with flexible operation times, sequence-dependent setup times and learning effect. International Journal of Production Economics, 141(1), 99-111. Doi: https://doi.org/10.1016/j.ijpe.2012.03.013
  52. Huang, Y., Sheng, B., Fu, G., Luo, R. ve Lu, Y. (2024). Multi-objective simulated annealing algorithm for robotic mixed-model two-sided assembly line balancing with setup times and multiple constraints. Applied Soft Computing, 156, 111507. Doi: https://doi.org/10.1016/j.asoc.2024.111507
  53. Janardhanan, M. N., Li, Z., Bocewicz, G., Banaszak, Z. ve Nielsen, P. (2019). Metaheuristic algorithms for balancing robotic assembly lines with sequence-dependent robot setup times. Applied Mathematical Modelling, 65, 256-270. Doi: https://doi.org/10.1016/j.apm.2018.08.016
  54. Khorram, M., Eghtesadifard, M. ve Niroomand, S. (2022). Hybrid meta-heuristic algorithms for U-shaped assembly line balancing problem with equipment and worker allocations. Soft Computing, 26(5), 2241-2258. Doi: https://doi.org/10.1007/s00500-021-06472-z
  55. Kılınçcı, Ö. (2023). Kaynak ve sıra bağımlı hazırlık süreli montaj hattı dengeleme problemi (KHMHDP). Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 38(1), 557-570. Doi: https://doi.org/10.17341/gazimmfd.757276
  56. Lahrichi, Y., Damand, D., Deroussi, L., Grangeon, N. ve Norre, S. (2023). Investigating two variants of the sequence-dependent robotic assembly line balancing problem by means of a split-based approach. International Journal of Production Research, 61(7), 2322-2338. Doi: https://doi.org/ 10.1080/00207543.2022.2062266
  57. Lee, A. H., Kang, H. Y. ve Chen, C. L. (2021). Multi-objective assembly line balancing problem with setup times using fuzzy goal programming and genetic algorithm. Symmetry, 13(2), 333. Doi: https://doi.org/ 10.3390/sym13020333
  58. Li, Z., Janardhanan, M. N., Tang, Q. ve Ponnambalam, S. G. (2019). Model and metaheuristics for robotic two-sided assembly line balancing problems with setup times. Swarm and Evolutionary Computation, 50, 100567. Doi: https://doi.org/10.1016/j.swevo.2019.100567
  59. Li, Z., Janardhanan, M. N. ve Ponnambalam, S. G. (2021). Cost-oriented robotic assembly line balancing problem with setup times: multi-objective algorithms. Journal of Intelligent Manufacturing, 32, 989-1007. Doi: https://doi.org/10.1007/s10845-020-01598-7
  60. Li, Z., Sikora, C. G. S. ve Kucukkoc, I. (2024). Chance-constrained stochastic assembly line balancing with branch, bound and remember algorithm. Annals of Operations Research, 335(1), 491-516. Doi: https://doi.org/ 10.1007/s10479-023-05809-1
  61. Martino, L. ve Pastor, R. (2010). Heuristic procedures for solving the general assembly line balancing problem with setups. International Journal of Production Research, 48(6), 1787-1804. Doi: https://doi.org/ 10.1080/00207540802577979
  62. Özcan, U. ve Toklu, B. (2010). Balancing two-sided assembly lines with sequence-dependent setup times. International Journal of Production Research, 48(18), 5363-5383. Doi: https://doi.org/10.1080/00207540903140750
  63. Özcan, U. (2019). Balancing and scheduling tasks in parallel assembly lines with sequence-dependent setup times. International Journal of Production Economics, 213, 81-96. Doi: https://doi.org/10.1016/j.ijpe.2019.02.023
  64. Rabbani, M., Mousavi, Z. ve Farrokhi-Asl, H. (2016a). Multi-objective metaheuristics for solving a type II robotic mixed-model assembly line balancing problem. Journal of Industrial and Production Engineering, 33(7), 472-484. Doi: https://doi.org/10.1080/21681015.2015.1126656
  65. Rabbani, M., Siadatian, R., Farrokhi-Asl, H. ve Manavizadeh, N. (2016b). Multi-objective optimization algorithms for mixed model assembly line balancing problem with parallel workstations. Cogent Engineering, 3(1), 1158903. Doi: https://doi.org/10.1080/23311916.2016.1158903
  66. Rabbani, M., Alipour, F., Farrokhi-Asl, H. ve Manavizadeh, N. (2018). Using metaheuristic algorithms for solving a mixed model assembly line balancing problem considering express parallel line and learning effect. Brazilian Journal of Operations & Production Management, 15(2), 254-269. Doi: https://doi.org/10.14488/BJOPM.2018.v15.n2.a8
  67. Samouei, P. ve Sobhishoja, M. (2023). Robust counterpart mathematical models for balancing, sequencing, and assignment of robotic U-shaped assembly lines with considering failures and setup times. OPSEARCH, 60(1), 87-124. Doi: https://doi.org/10.1007/s12597-022-00609-w
  68. Seyed-Alagheband, S. A., Ghomi, S. F. ve Zandieh, M. (2011). A simulated annealing algorithm for balancing the assembly line type II problem with sequence-dependent setup times between tasks. International Journal of Production Research, 49(3), 805-825. Doi: https://doi.org/10.1080/ 00207540903471486
  69. Scholl, A., Boysen, N. ve Fliedner, M. (2013). The assembly line balancing and scheduling problem with sequence-dependent setup times: problem extension, model formulation and efficient heuristics. OR spectrum, 35, 291-320. Doi: https://doi.org/10.1007/s00291-011-0265-0
  70. Sivasankaran, P. ve Shahabudeen, P. (2014). Literature review of assembly line balancing problems. The International Journal of Advanced Manufacturing Technology, 73, 1665-1694. Doi: https://doi.org/10.1007/s00170-014-5944-y
  71. Ustun, O. (2012). Multi-choice goal programming formulation based on the conic scalarizing function. Applied Mathematical Modelling, 36(3), 974-988. Doi: https://doi.org/10.1016/j.apm.2011.07.065
  72. Yang, W. ve Cheng, W. (2020a). A Mathematical Model and a Simulated Annealing Algorithm for Balancing Multi‐manned Assembly Line Problem with Sequence‐Dependent Setup Time. Mathematical problems in Engineering, 2020(1), 8510253. Doi: https://doi.org/10.1155/2020/8510253
  73. Yang, W. ve Cheng, W. (2020b). Modelling and solving mixed-model two-sided assembly line balancing problem with sequence-dependent setup time. International Journal of Production Research, 58(21), 6638-6659. Doi: https://doi.org/10.1080/00207543.2019.1683255
  74. Yilmaz, H. (2021). Modeling and solving assembly line worker assignment and balancing problem with sequence-dependent setup times.Soft Computing, 25(20), 12899-12914. Doi: https://doi.org/10.1007/s00500-021-06107-3
  75. Yolmeh, A. ve Kianfar, F. (2012). An efficient hybrid genetic algorithm to solve assembly line balancing problem with sequence-dependent setup times. Computers & industrial engineering, 62(4), 936-945. Doi: https://doi.org/10.1016/j.cie.2011.12.017
  76. Yoosefelahi, A., Aminnayeri, M., Mosadegh, H. ve Ardakani, H. D. (2012). Type II robotic assembly line balancing problem: An evolution strategies algorithm for a multi-objective model. Journal of Manufacturing Systems, 31(2), 139-151. Doi: https://doi.org/10.1016/j.jmsy.2011.10.002