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Esnek Akış Tipi Çizelgeleme Problemlerinin Araştırılması: Bibliyometrik Analiz

Yıl 2025, Cilt: 8 Sayı: 5, 2133 - 2150, 15.12.2025
https://doi.org/10.47495/okufbed.1629196

Öz

Akış tipi çizelgelemenin, en az bir aşamasında, birden fazla makinen yer aldığı problem, Esnek akış tipi olarak isimlendirilmektedir. Bu araştırmada 1995 yılından günümüze kadar Esnek akış tipi çizelgeleme problemleri ile ilgili literatürde yapılan çalışmalar incelenmiştir. Esnek akış tipi çizelgeleme problemlerinin son 30 yıldaki gelişimi bibliyometrik analiz yardımıyla belirlenmeye çalışılmıştır. Bibliyometrik analiz, bilimsel literatürdeki yayınları, atıfları ve diğer ölçümleri inceleyerek bir alanın gelişimini değerlendirir. Bibliyometrik analizde, “Scopus” veri tabanından “Hybrid Flow Shop Scheduling Problems” anahtar kelimesiyle sorgu yapılmış ve analizler R-Studio programında Bibliometrix paketi kullanılarak gerçekleştirilmiştir. Toplam 766 belge incelenmiş, bu belgelere toplam 20 620 atıf yapıldığı tespit edilmiştir. Yıllık büyüme oranın %3,73 olduğu hesaplanmıştır. Araştırma sonucunda, Çin, ABD ve Avrupa’daki bilim insanları tarafından bu alanda önemli çalışmalar yapıldığı görülmüştür. Bu çalışmanın sonuçları, Esnek akış tipi çizelgeleme problemleri üzerine yapılan araştırmaların geniş bir coğrafi dağılıma sahip olduğunu ve disiplinler arası bir yaklaşımı teşvik ettiğini ortaya koymuştur.

Kaynakça

  • Akkoyunlu MC., Engin O., Büyüközkan K. A harmony search algorithm for hybrid flow shop scheduling with multiprocessor task problems. Proceedings of the 6th International Conference on Modeling, Simulation, and Applied Optimization (ICMSAO), 27-29 Mayıs 2015, 1-3., İstanbul. DOI:10.1109/ICMSAO.2015.7152245
  • Alaykıran K., Engin O., Döyen A. Using ant colony optimization to solve hybrid flow shop scheduling problems. International Journal of Advanced Manufacturing Technology 2007; 35: 541-550. https://doi.org/10.1007/s00170-007-1048-2
  • Başar R., Büyüközkan K., Engin O. Distributed no-wait flow shop with fuzzy environment. In: Kahraman C., Tolga AC., Cevik Onar S., Cebi S., Oztaysi B., Sari IU. (eds) Intelligent and Fuzzy Systems. INFUS 2022. Lecture Notes in Networks and Systems, vol 504. Springer, Cham. https://doi.org/10.1007/978-3-031-09173-5_35
  • Başar R., Engin O. A hybrid scatter search method for solving fuzzy no-wait flow-shop scheduling problems. Engineering Optimization 2024; 1-34. https://doi.org/10.1080/0305215X.2024.2367600
  • Baysal ME., Sarucan A., Büyüközkan K., Engin O. Artificial bee colony algorithm for solving multi-objective distributed fuzzy permutation flow shop problem. Journal of Intelligent & Fuzzy Systems 2021; 42(1): 439-449. https://doi.org/10.3233/JIFS-219202
  • Bozorgirad MA., Logendran R. A comparison of local search algorithms with population-based algorithms in hybrid flow shop scheduling problems with realistic characteristics. International Journal of Advanced Manufacturing Technology 2016; 83: 1135-1151.
  • Cui Z., Gu X. An improved discrete artificial bee colony algorithm to minimize the makespan on hybrid flow shop problems. Neurocomputing 2015; 148: 248-259. https://doi.org/10.1016/j.neucom.2013.07.056
  • Engin BE., Engin O. A new memetic global and local search algorithm for solving hybrid flow shop with multiprocessor task scheduling problem. SN Applied Sciences 2020; 2: 2059.
  • Engin O., Döyen A. A new approach to solve hybrid flow shop scheduling problems by artificial immune system. Future Generation Computer Systems 2004; 20: 1083-1095. https://doi.org/10.1016/j.future.2004.03.014
  • Engin O., Durmaz T., Baysal ME., Sarucan A. Çok kademeli montaj operasyonlu esnek akış tipi çizelgeleme probleminin çözümü için bir paralel kanguru algoritması. 6th International GAP Engineering Congress, 23-25 Ekim 2018, 325-329, Şanlıurfa.
  • Engin O., Engin B. Hybrid flow shop with multiprocessor task scheduling based on earliness and tardiness penalties. Journal of Enterprise Information Management 2018; 31(6): 925-936.
  • Engin O., İşler M. An efficient parallel greedy algorithm for fuzzy hybrid flow shop scheduling with setup time and lot size: A case study in apparel process. Journal of Fuzzy Extension and Applications 2022; 3(3): 249-262. https://doi.org/10.22105/jfea.2021.314312.1169
  • Engin O., Özmete A., İpek S., Karaoğlu YE. Çizelgeleme problemlerinin çözümünde hibrit biyocoğrafya tabanlı optimizasyon algoritmasının kullanımı. Harran Üniversitesi Mühendislik Dergisi 2023; 8(1): 68-77. https://doi.org/10.46578/humder.1256671
  • Engin O., Sarıcan B. Makine çizelgeleme problemlerinin çözümünde pekiştirmeli öğrenme eksinin analizi. ALKU Journal of Science 2024; 6(2): 116-140. https://doi.org/10.46740/alku.1390397
  • Engin O., Yılmaz MK. A fuzzy logic based methodology for multi-objective hybrid flow shop scheduling with multi-processor tasks problems and solving with an efficient genetic algorithm. Journal of Intelligent & Fuzzy Systems 2021; 42(1): 451-463. https://doi.org/10.3233/JIFS-21920
  • Fan B., Yang W., Zhang Z. Solving the two-stage hybrid flow shop scheduling problem based on mutant firefly algorithm. J Ambient Intell Human Comput 2019; 10: 979-990. https://doi.org/10.1007/s12652-018-0903-3
  • Güler G. A bibliometric analysis of power analysis studies. Journal of Measurement and Evaluation in Education and Psychology. 2023. 14(3): 235-248. https://doi.org/10.21031/epod.1343984
  • Hajji MK., Hamlaoui O., Hadda H. A simulated annealing metaheuristic approach to hybrid flow shop scheduling problem. Advances in Industrial and Manufacturing Engineering 2024; 9. https://doi.org/10.1016/j.aime.2024.100144
  • İşler M., Engin O. Fuzzy hybrid flow shop scheduling problem: an application. In: Kahraman C., Cebi S., Cevik Onar S., Oztaysi B., Tolga AC., Sari I.U. (ed) Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation INFUS 2021 Lecture Notes in Networks and Systems. Springer 2022; 307. https://doi.org/10.1007/978-3-030-85626-7_73
  • Kahraman C., Engin O., Kaya I., Yılmaz MK. An application of effective genetic algorithms for solving hybrid flow shop scheduling problems. International Journal of Computational Intelligence Systems 2008; 1: 134-147. https://doi.org/10.2991/ijcis.2008.1.2.4
  • Liao CJ., Tjandradjaja E., Chung TP. An approach using particle swarm optimization and bottleneck heuristic to solve hybrid flow shop scheduling problem. Applied Soft Computing 2012; 12: 1755-1764. https://doi.org/10.1016/j.asoc.2012.01.011
  • Li X., Guo X., Tang H., Wu R., Liu J. An improved cuckoo search algorithm for the hybrid flow-shop scheduling problem in sand casting enterprises considering batch processing. Computers & Industrial Engineering 2023; 176. https://doi.org/10.1016/j.cie.2022.108921
  • Li JK., Li RH., Li JQ., Yu X., Xu Y. A multi-dimensional co-evolutionary algorithm for multi-objective resource-constrained flexible flowshop with robotic transportation, Applied Soft Computing 2025, 170: 1- 23. https://doi.org/10.1016/j.asoc.2024.112689.
  • Marichelvam MK., Prabaharan T., Yang XS. Improved cuckoo search algorithm for hybrid flow shop scheduling problems to minimize makespan. Applied Soft Computing 2014; 19: 93-101.
  • Qin HX., Han YY., Zhang B., Meng LL., Liu YP., Pan QK., Gong DW. An improved iterated greedy algorithm for the energy-efficient blocking hybrid flow shop scheduling problem. Swarm and Evolutionary Computation 2022; 69. https://doi.org/10.1016/j.swevo.2021.100992.
  • Tang L., Liu W., Liu J. A Neural network model and algorithm for the hybrid flow shop scheduling problem in a dynamic environment. J. Intell. Manuf. 2005; 16: 361-370. https://doi.org/10.1007/s10845-005-7029-0
  • Ullah W., Ab Rashid MFF., Mu’tasim MAN. Greedy-assisted teaching-learning-based optimization algorithm for cost-based hybrid flow shop scheduling. Expert Systems with Applications 2025; 273, 1-15. https://doi.org/10.1016/j.eswa.2025.126955
  • Vidojević F., Džamić A., Džamić D., Marić M. A novel artificial intelligence search algorithm and mathematical model for the hybrid flow shop scheduling problem. J Big Data 2025; 12, 23.
  • Wang J., Lei D., Li D., Li X., Tang H. A dynamic artificial bee colony for fuzzy distributed energy-efficient hybrid flow shop scheduling with batch processing machines. Journal of Manufacturing Systems, 2025; 78: 94-108. https://doi.org/10.1016/j.jmsy.2024.10.019
  • Yiğit G., Engin O. Endüstri 5.0 ile sürdürülebilirliğin sağlanması: bir bibliyometrik analiz. İstanbul Aydın Üniversitesi Sosyal Bilimler Dergisi 2025; 17(1): 23-46.
  • Yu C., Andreotti P., Semeraro Q. Multi-objective scheduling in hybrid flow shop: Evolutionary algorithms using multi-decoding framework. Computers & Industrial Engineering 2020; 147. https://doi.org/10.1016/j.cie.2020.106570
  • Zhang B., Pan Q., Gao L., Zhang X., Sang H., Li J. An effective modified migrating birds optimization for hybrid flow shop scheduling problem with lot streaming. Applied Soft Computing 2017; 52: 14-27. https://doi.org/10.1016/j.asoc.2016.12.021
  • Zhang C., Tan J., Peng K., Gao L., Shen W., Lian K. A discrete whale swarm algorithm for hybrid flow-shop scheduling problem with limited buffers. Robotics and Computer-Integrated Manufacturing 2021; 68. https://doi.org/10.1016/j.rcim.2020.102081
  • Zhou B., Hu L., Zhong Z. A hybrid differential evolution algorithm with estimation of distribution algorithm for reentrant hybrid flow shop scheduling problem. Neural Computing and Applications 2018; 30: 193-209. https://doi.org/10.1007/s00521-016-2692-y

Investigation of the Hybrid Flowshop Scheduling Problems: Bibliometric Analysis

Yıl 2025, Cilt: 8 Sayı: 5, 2133 - 2150, 15.12.2025
https://doi.org/10.47495/okufbed.1629196

Öz

The problem with more than one machine is involved in at least one stage of the flow type scheduling is called Hybrid Flow Type. In this study, an analysis is conducted on the literature pertaining to hybrid flow type scheduling issues since 1995. The determination of the evolution of hybrid flow type scheduling issues over the past 30 years has been attempted through the utilization of bibliometric analysis. Bibliometric analysis evaluates the development of a field by examining publications, citations and other metrics in scientific literature. In the bibliometric analysis, a query was made from the “Scopus” database with the keyword “Hybrid Flow Shop Scheduling Problems” and the analysis was performed using the Bibliometrix package in the R-Studio program. A total of 766 documents were analyzed, and it was determined that 20 620 citations were made to these documents. The annual growth rate was calculated to be 3.73%. The results of the research show that significant work has been done in this area by researchers from China, the United States, and Europe. The findings of this study demonstrate that research on scheduling problems of hybrid flow type exhibits a diverse geographical distribution and encourages an interdisciplinary approach.

Kaynakça

  • Akkoyunlu MC., Engin O., Büyüközkan K. A harmony search algorithm for hybrid flow shop scheduling with multiprocessor task problems. Proceedings of the 6th International Conference on Modeling, Simulation, and Applied Optimization (ICMSAO), 27-29 Mayıs 2015, 1-3., İstanbul. DOI:10.1109/ICMSAO.2015.7152245
  • Alaykıran K., Engin O., Döyen A. Using ant colony optimization to solve hybrid flow shop scheduling problems. International Journal of Advanced Manufacturing Technology 2007; 35: 541-550. https://doi.org/10.1007/s00170-007-1048-2
  • Başar R., Büyüközkan K., Engin O. Distributed no-wait flow shop with fuzzy environment. In: Kahraman C., Tolga AC., Cevik Onar S., Cebi S., Oztaysi B., Sari IU. (eds) Intelligent and Fuzzy Systems. INFUS 2022. Lecture Notes in Networks and Systems, vol 504. Springer, Cham. https://doi.org/10.1007/978-3-031-09173-5_35
  • Başar R., Engin O. A hybrid scatter search method for solving fuzzy no-wait flow-shop scheduling problems. Engineering Optimization 2024; 1-34. https://doi.org/10.1080/0305215X.2024.2367600
  • Baysal ME., Sarucan A., Büyüközkan K., Engin O. Artificial bee colony algorithm for solving multi-objective distributed fuzzy permutation flow shop problem. Journal of Intelligent & Fuzzy Systems 2021; 42(1): 439-449. https://doi.org/10.3233/JIFS-219202
  • Bozorgirad MA., Logendran R. A comparison of local search algorithms with population-based algorithms in hybrid flow shop scheduling problems with realistic characteristics. International Journal of Advanced Manufacturing Technology 2016; 83: 1135-1151.
  • Cui Z., Gu X. An improved discrete artificial bee colony algorithm to minimize the makespan on hybrid flow shop problems. Neurocomputing 2015; 148: 248-259. https://doi.org/10.1016/j.neucom.2013.07.056
  • Engin BE., Engin O. A new memetic global and local search algorithm for solving hybrid flow shop with multiprocessor task scheduling problem. SN Applied Sciences 2020; 2: 2059.
  • Engin O., Döyen A. A new approach to solve hybrid flow shop scheduling problems by artificial immune system. Future Generation Computer Systems 2004; 20: 1083-1095. https://doi.org/10.1016/j.future.2004.03.014
  • Engin O., Durmaz T., Baysal ME., Sarucan A. Çok kademeli montaj operasyonlu esnek akış tipi çizelgeleme probleminin çözümü için bir paralel kanguru algoritması. 6th International GAP Engineering Congress, 23-25 Ekim 2018, 325-329, Şanlıurfa.
  • Engin O., Engin B. Hybrid flow shop with multiprocessor task scheduling based on earliness and tardiness penalties. Journal of Enterprise Information Management 2018; 31(6): 925-936.
  • Engin O., İşler M. An efficient parallel greedy algorithm for fuzzy hybrid flow shop scheduling with setup time and lot size: A case study in apparel process. Journal of Fuzzy Extension and Applications 2022; 3(3): 249-262. https://doi.org/10.22105/jfea.2021.314312.1169
  • Engin O., Özmete A., İpek S., Karaoğlu YE. Çizelgeleme problemlerinin çözümünde hibrit biyocoğrafya tabanlı optimizasyon algoritmasının kullanımı. Harran Üniversitesi Mühendislik Dergisi 2023; 8(1): 68-77. https://doi.org/10.46578/humder.1256671
  • Engin O., Sarıcan B. Makine çizelgeleme problemlerinin çözümünde pekiştirmeli öğrenme eksinin analizi. ALKU Journal of Science 2024; 6(2): 116-140. https://doi.org/10.46740/alku.1390397
  • Engin O., Yılmaz MK. A fuzzy logic based methodology for multi-objective hybrid flow shop scheduling with multi-processor tasks problems and solving with an efficient genetic algorithm. Journal of Intelligent & Fuzzy Systems 2021; 42(1): 451-463. https://doi.org/10.3233/JIFS-21920
  • Fan B., Yang W., Zhang Z. Solving the two-stage hybrid flow shop scheduling problem based on mutant firefly algorithm. J Ambient Intell Human Comput 2019; 10: 979-990. https://doi.org/10.1007/s12652-018-0903-3
  • Güler G. A bibliometric analysis of power analysis studies. Journal of Measurement and Evaluation in Education and Psychology. 2023. 14(3): 235-248. https://doi.org/10.21031/epod.1343984
  • Hajji MK., Hamlaoui O., Hadda H. A simulated annealing metaheuristic approach to hybrid flow shop scheduling problem. Advances in Industrial and Manufacturing Engineering 2024; 9. https://doi.org/10.1016/j.aime.2024.100144
  • İşler M., Engin O. Fuzzy hybrid flow shop scheduling problem: an application. In: Kahraman C., Cebi S., Cevik Onar S., Oztaysi B., Tolga AC., Sari I.U. (ed) Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation INFUS 2021 Lecture Notes in Networks and Systems. Springer 2022; 307. https://doi.org/10.1007/978-3-030-85626-7_73
  • Kahraman C., Engin O., Kaya I., Yılmaz MK. An application of effective genetic algorithms for solving hybrid flow shop scheduling problems. International Journal of Computational Intelligence Systems 2008; 1: 134-147. https://doi.org/10.2991/ijcis.2008.1.2.4
  • Liao CJ., Tjandradjaja E., Chung TP. An approach using particle swarm optimization and bottleneck heuristic to solve hybrid flow shop scheduling problem. Applied Soft Computing 2012; 12: 1755-1764. https://doi.org/10.1016/j.asoc.2012.01.011
  • Li X., Guo X., Tang H., Wu R., Liu J. An improved cuckoo search algorithm for the hybrid flow-shop scheduling problem in sand casting enterprises considering batch processing. Computers & Industrial Engineering 2023; 176. https://doi.org/10.1016/j.cie.2022.108921
  • Li JK., Li RH., Li JQ., Yu X., Xu Y. A multi-dimensional co-evolutionary algorithm for multi-objective resource-constrained flexible flowshop with robotic transportation, Applied Soft Computing 2025, 170: 1- 23. https://doi.org/10.1016/j.asoc.2024.112689.
  • Marichelvam MK., Prabaharan T., Yang XS. Improved cuckoo search algorithm for hybrid flow shop scheduling problems to minimize makespan. Applied Soft Computing 2014; 19: 93-101.
  • Qin HX., Han YY., Zhang B., Meng LL., Liu YP., Pan QK., Gong DW. An improved iterated greedy algorithm for the energy-efficient blocking hybrid flow shop scheduling problem. Swarm and Evolutionary Computation 2022; 69. https://doi.org/10.1016/j.swevo.2021.100992.
  • Tang L., Liu W., Liu J. A Neural network model and algorithm for the hybrid flow shop scheduling problem in a dynamic environment. J. Intell. Manuf. 2005; 16: 361-370. https://doi.org/10.1007/s10845-005-7029-0
  • Ullah W., Ab Rashid MFF., Mu’tasim MAN. Greedy-assisted teaching-learning-based optimization algorithm for cost-based hybrid flow shop scheduling. Expert Systems with Applications 2025; 273, 1-15. https://doi.org/10.1016/j.eswa.2025.126955
  • Vidojević F., Džamić A., Džamić D., Marić M. A novel artificial intelligence search algorithm and mathematical model for the hybrid flow shop scheduling problem. J Big Data 2025; 12, 23.
  • Wang J., Lei D., Li D., Li X., Tang H. A dynamic artificial bee colony for fuzzy distributed energy-efficient hybrid flow shop scheduling with batch processing machines. Journal of Manufacturing Systems, 2025; 78: 94-108. https://doi.org/10.1016/j.jmsy.2024.10.019
  • Yiğit G., Engin O. Endüstri 5.0 ile sürdürülebilirliğin sağlanması: bir bibliyometrik analiz. İstanbul Aydın Üniversitesi Sosyal Bilimler Dergisi 2025; 17(1): 23-46.
  • Yu C., Andreotti P., Semeraro Q. Multi-objective scheduling in hybrid flow shop: Evolutionary algorithms using multi-decoding framework. Computers & Industrial Engineering 2020; 147. https://doi.org/10.1016/j.cie.2020.106570
  • Zhang B., Pan Q., Gao L., Zhang X., Sang H., Li J. An effective modified migrating birds optimization for hybrid flow shop scheduling problem with lot streaming. Applied Soft Computing 2017; 52: 14-27. https://doi.org/10.1016/j.asoc.2016.12.021
  • Zhang C., Tan J., Peng K., Gao L., Shen W., Lian K. A discrete whale swarm algorithm for hybrid flow-shop scheduling problem with limited buffers. Robotics and Computer-Integrated Manufacturing 2021; 68. https://doi.org/10.1016/j.rcim.2020.102081
  • Zhou B., Hu L., Zhong Z. A hybrid differential evolution algorithm with estimation of distribution algorithm for reentrant hybrid flow shop scheduling problem. Neural Computing and Applications 2018; 30: 193-209. https://doi.org/10.1007/s00521-016-2692-y
Toplam 34 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Esnek İmalat Sistemleri
Bölüm Araştırma Makalesi
Yazarlar

Celal Merdane 0009-0005-1203-9759

Kamil Çölbay 0009-0001-7834-9179

Orhan Engin 0000-0002-7250-0317

Gönderilme Tarihi 29 Ocak 2025
Kabul Tarihi 26 Mayıs 2025
Yayımlanma Tarihi 15 Aralık 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 8 Sayı: 5

Kaynak Göster

APA Merdane, C., Çölbay, K., & Engin, O. (2025). Esnek Akış Tipi Çizelgeleme Problemlerinin Araştırılması: Bibliyometrik Analiz. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 8(5), 2133-2150. https://doi.org/10.47495/okufbed.1629196
AMA Merdane C, Çölbay K, Engin O. Esnek Akış Tipi Çizelgeleme Problemlerinin Araştırılması: Bibliyometrik Analiz. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi. Aralık 2025;8(5):2133-2150. doi:10.47495/okufbed.1629196
Chicago Merdane, Celal, Kamil Çölbay, ve Orhan Engin. “Esnek Akış Tipi Çizelgeleme Problemlerinin Araştırılması: Bibliyometrik Analiz”. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi 8, sy. 5 (Aralık 2025): 2133-50. https://doi.org/10.47495/okufbed.1629196.
EndNote Merdane C, Çölbay K, Engin O (01 Aralık 2025) Esnek Akış Tipi Çizelgeleme Problemlerinin Araştırılması: Bibliyometrik Analiz. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi 8 5 2133–2150.
IEEE C. Merdane, K. Çölbay, ve O. Engin, “Esnek Akış Tipi Çizelgeleme Problemlerinin Araştırılması: Bibliyometrik Analiz”, Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi, c. 8, sy. 5, ss. 2133–2150, 2025, doi: 10.47495/okufbed.1629196.
ISNAD Merdane, Celal vd. “Esnek Akış Tipi Çizelgeleme Problemlerinin Araştırılması: Bibliyometrik Analiz”. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi 8/5 (Aralık2025), 2133-2150. https://doi.org/10.47495/okufbed.1629196.
JAMA Merdane C, Çölbay K, Engin O. Esnek Akış Tipi Çizelgeleme Problemlerinin Araştırılması: Bibliyometrik Analiz. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi. 2025;8:2133–2150.
MLA Merdane, Celal vd. “Esnek Akış Tipi Çizelgeleme Problemlerinin Araştırılması: Bibliyometrik Analiz”. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi, c. 8, sy. 5, 2025, ss. 2133-50, doi:10.47495/okufbed.1629196.
Vancouver Merdane C, Çölbay K, Engin O. Esnek Akış Tipi Çizelgeleme Problemlerinin Araştırılması: Bibliyometrik Analiz. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi. 2025;8(5):2133-50.

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