@article{MTMT:34631848,
	title = {A Coordinated Supply Contract for a Two-Echelon Supply Chain Considering Learning Effects},
	url = {https://m2.mtmt.hu/api/publication/34631848},
	author = {Tao, Ze-Jin and Koo, Pyung-Hoi},
	doi = {10.3390/app14041513},
	journal-iso = {APPL SCI-BASEL},
	journal = {APPLIED SCIENCES-BASEL},
	volume = {14},
	unique-id = {34631848},
	abstract = {In a supply chain composed of multiple members, supply chain coordination plays a crucial role in achieving overall optimization and efficiency. Various supply contract forms have been studied in the existing literature to facilitate supply chain coordination. However, most existing literature has established coordination models assuming constant production costs. In reality, per-unit production costs often decrease as production quantity increases, which is called the learning effect. This paper underscores the significance of considering this learning effect in decision-making processes for coordinated supply contracts. We propose a supply contract scheme for channel coordination that incorporates the learning effect within a supply chain comprising a single manufacturer and a single retailer. In this framework, the manufacturer acts as a Stackelberg leader, initiating the process by designing and presenting the contract. The supply contract scheme is designed to ensure that the retailer’s order quantity aligns with the global solution. We also demonstrate how the contract parameters are determined when the relative bargaining powers of the supply chain members are given exogenously in the market. Our findings reveal that contracts with a learning curve can generate additional profits for both the manufacturer and the retailer compared to the existing coordinated contracts with static production costs. This study provides valuable insights into the impact of the learning effect on supply chain efficiency and offers practical implications for supply chain practitioners.},
	year = {2024},
	eissn = {2076-3417},
	orcid-numbers = {Tao, Ze-Jin/0009-0006-9522-4702; Koo, Pyung-Hoi/0000-0002-1695-3039}
}

@article{MTMT:34505210,
	title = {Enhancing efficiency and adaptability in mixed model line balancing through the fusion of learning effects and worker prerequisites},
	url = {https://m2.mtmt.hu/api/publication/34505210},
	author = {Alhomaidhi, Esam},
	doi = {10.5267/j.ijiec.2023.12.008},
	journal-iso = {INTL JL INDUST ENG COMPUT},
	journal = {INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING COMPUTATIONS},
	unique-id = {34505210},
	issn = {1923-2926},
	abstract = {This research introduces a comprehensive scheme to tackle the Mixed-Model Assembly Line Balancing Problem (MALBPLW) within manufacturing contexts. The primary aim is to optimize assembly line task assignments by integrating both the learning effect and worker prerequisites. The learning effect recognizes the enhanced efficiency of workers over time due to learning and experience. A novel mathematical model and solution approach are proposed, encompassing factors like cycle time, task interdependencies, worker classifications, and the learning effect. The model endeavors to minimize the overall costs related to both workers and workstations while simultaneously maximizing production efficiency. Experimental assessments are conducted to evaluate the efficacy of this proposed approach. Diverse manufacturing scenarios are inspected, comparing and analyzing cost reductions and production efficiency. The outcomes highlight the effectiveness of this approach in achieving enhanced cost-effectiveness and resource utilization in contrast to conventional methods. This study contributes significantly to advancing assembly line balancing and production planning techniques by presenting a pragmatic framework for optimizing resource usage and reducing costs in manufacturing environments. The knowledge extracted from these discoveries can significantly assist professionals in the industry seeking to improve manufacturing processes and strengthen competitiveness. (c) 2024 by the authors; licensee Growing Science, Canada},
	keywords = {Heuristic; Engineering, Industrial; Learning Effect; Mixed-model Line balancing; Task requirements},
	year = {2023},
	eissn = {1923-2934}
}

@article{MTMT:33263126,
	title = {Mixed-model assembly line balancing problem considering learning effect and uncertain demand},
	url = {https://m2.mtmt.hu/api/publication/33263126},
	author = {Li, Yuchen and Liu, Dan and Kucukkoc, Ibrahim},
	doi = {10.1016/j.cam.2022.114823},
	journal-iso = {J COMPUT APPL MATH},
	journal = {JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS},
	volume = {422},
	unique-id = {33263126},
	issn = {0377-0427},
	year = {2023},
	eissn = {1879-1778}
}

@article{MTMT:33591977,
	title = {Hybridizations in line balancing problems: A comprehensive review on new trends and formulations},
	url = {https://m2.mtmt.hu/api/publication/33591977},
	author = {Battaïa, Olga and Dolgui, Alexandre},
	doi = {10.1016/j.ijpe.2022.108673},
	journal-iso = {INT J PROD ECON},
	journal = {INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS},
	volume = {250},
	unique-id = {33591977},
	issn = {0925-5273},
	year = {2022},
	eissn = {1873-7579},
	orcid-numbers = {Dolgui, Alexandre/0000-0003-0527-4716}
}

@article{MTMT:33267116,
	title = {How cognitive automation of marketing activities can transform the processes of a financial institution},
	url = {https://m2.mtmt.hu/api/publication/33267116},
	author = {Jensolin, J. and Gotmare, P.R},
	journal-iso = {ACAD MARKET STUD J},
	journal = {ACADEMY OF MARKETING STUDIES JOURNAL},
	volume = {26},
	unique-id = {33267116},
	issn = {1095-6298},
	year = {2022},
	eissn = {1528-2678},
	pages = {1-3}
}

@{MTMT:33267120,
	title = {ALBP Under Learning Effect and Uncertain Demand},
	url = {https://m2.mtmt.hu/api/publication/33267120},
	author = {Li, Y.},
	booktitle = {Assembly Line Balancing under Uncertain Task Time and Demand Volatility},
	doi = {10.1007/978-981-19-4215-0_5},
	volume = {8},
	unique-id = {33267120},
	abstract = {In a mixed assembly line balancing problem, tasks belonging to different product models, are allocated to workstations according to their processing times and precedence relationships amongst tasks. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.},
	keywords = {Product models; Processing Time; BALANCING; Uncertain demand; Learning effects; Assembly line balancing problems; Mixed assemblies; Precedence relationships},
	year = {2022},
	pages = {89-110}
}

@inproceedings{MTMT:34067449,
	title = {Learning Effect and Its Applications in Production, Operation and Maintenance: A Literature Review},
	url = {https://m2.mtmt.hu/api/publication/34067449},
	author = {Luo, J.-Z. and Su, C.},
	booktitle = {12th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE 2022)},
	doi = {10.1049/icp.2022.3139},
	unique-id = {34067449},
	abstract = {The theory of learning effect has gained great interest as a tool to analyze and predict the performance of individuals or organizations. The unique and beneficial characteristics of learning curve models allow more scientific improvement for the planning, organizing and management activities, thus leading to a more efficient system operation. This review focuses on the applications of learning effect in three areas of industrial engineering, including the production scheduling, operation management and maintenance decision-making. In this review, the concept of learning effect and its development process are briefly introduced. After that, a comparison of different commonly used learning and forgetting effect models is conducted. Furthermore, we review and summarize the application of learning effect in industrial engineering in a more comprehensive way. Finally, the limitations of the current studies and possible practical application are discussed. It can be concluded that learning effect is valuable to be applied in the operation and maintenance process of manufacturing system. © 2022 IEEE.},
	keywords = {PERFORMANCE; Learning systems; MAINTENANCE; MAINTENANCE; production control; decision making; Literature reviews; ITS applications; learning curves; Operation management; Operation management; Learning Effect; Learning effects; production scheduling; production scheduling; forgetting effect; forgetting effect; Production/operations and maintenances; Theories of learning},
	year = {2022},
	pages = {1904-1910}
}

@article{MTMT:32113368,
	title = {Economic production lot sizing under imperfect quality, on-line inspection, and inspection errors: Full vs. sampling inspection},
	url = {https://m2.mtmt.hu/api/publication/32113368},
	author = {Bose, Dipankar and Guha, Apratim},
	doi = {10.1016/j.cie.2021.107565},
	journal-iso = {COMPUT IND ENG},
	journal = {COMPUTERS AND INDUSTRIAL ENGINEERING},
	volume = {160},
	unique-id = {32113368},
	issn = {0360-8352},
	year = {2021},
	eissn = {1879-0550}
}

@article{MTMT:31909328,
	title = {Evaluating the effect of learning rate, batch size and assignment strategies on the production performance},
	url = {https://m2.mtmt.hu/api/publication/31909328},
	author = {Bruno, Giulia and Antonelli, Dario and Stadnicka, Dorota},
	doi = {10.1080/21681015.2021.1883133},
	journal-iso = {J IND PROD ENG},
	journal = {JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING},
	volume = {38},
	unique-id = {31909328},
	issn = {2168-1015},
	year = {2021},
	eissn = {2168-1023},
	pages = {137-147}
}

@article{MTMT:32477849,
	title = {Simulation and optimization model for a cross-docking distribution center: Case study of a railway business},
	url = {https://m2.mtmt.hu/api/publication/32477849},
	author = {Chaiyarot, M. and Pitiruek, K.},
	doi = {10.14456/apst.2021.34},
	journal-iso = {Asia-Pacific Journal of Science and Technology},
	journal = {Asia-Pacific Journal of Science and Technology},
	volume = {26},
	unique-id = {32477849},
	abstract = {One of the various issues experienced in execution of manufacturing systems in supply chain management is the bottleneck. Bottlenecks frequently occur during operation of real systems. Railway businesses encounter the same issue. In this research, simulation models were developed to explore and eliminate bottlenecks to improve the internal production zone of a rail freight cross-docking center (RFCDC) distributing goods to customers. This research developed the proposed model using ARENA software and performance criteria. Assessment considered data about the output of finished goods, the work-in-process holding inventory, the maximum net profit, and the average total time required. The proposed model demonstrated the best results considering all criteria and compared them to a real operation system, revealing 28.2%, 99.7%, 41.4% and 99.5% improvement in finished goods capacity, work-in-progress, profit and total process time, respectively. The proposed model is recommended for implementation in the RFCDC of this case study as a decision tool for resource allocation and planning. © 2021, Khon Kaen University,Research and Technology Transfer Affairs Division. All rights reserved.},
	keywords = {resource allocation; ARENA simulation; Rail distribution; Rail freight cross-docking},
	year = {2021},
	eissn = {2539-6293}
}

@article{MTMT:32594848,
	title = {Analisis Sensitivitas Penurunan Waktu Produksi untuk Memaksimalkan Produk jadi Sektor Konstruksi dengan Mempertimbangkan Keseimbangan Lintasan},
	url = {https://m2.mtmt.hu/api/publication/32594848},
	author = {Glisina, Dwinoor Rembulan and Kartika, Nur Alfina and Filscha, Nurprihatin},
	journal-iso = {JIES},
	journal = {Journal of Industrial and Engineering System},
	volume = {2},
	unique-id = {32594848},
	year = {2021},
	eissn = {2722-7979},
	pages = {122-127}
}

@article{MTMT:32069908,
	title = {An exact solution method for solving seru scheduling problems with past-sequence-dependent setup time and learning effect},
	url = {https://m2.mtmt.hu/api/publication/32069908},
	author = {Jiang, Y. and Zhang, Z. and Gong, X. and Yin, Y.},
	doi = {10.1016/j.cie.2021.107354},
	journal-iso = {COMPUT IND ENG},
	journal = {COMPUTERS AND INDUSTRIAL ENGINEERING},
	volume = {158},
	unique-id = {32069908},
	issn = {0360-8352},
	abstract = {This paper concentrates on three scheduling problems with past-sequence-dependent setup time and DeJong's learning effect in seru production system (SPS), including minimizing the total waiting time, the total absolute differences in waiting time, and the total load. The setup time, which is dependent on the seru and jobs that have been processed, is considered. Also, the actual processing time with DeJong's learning effect is concerned. We propose a general exact solution method to show these three problems can be transformed into assignment problems and can be solved in polynomial time. Finally, the computational experiments are made to validate that the proposed method is promising in solving seru scheduling problems effectively. © 2021 Elsevier Ltd},
	keywords = {Learning Effect; setup time; Exact solution method; Seru scheduling},
	year = {2021},
	eissn = {1879-0550}
}

@article{MTMT:31276687,
	title = {Balancing, sequencing, and job rotation scheduling of a U-shaped lean cell with dynamic operator performance},
	url = {https://m2.mtmt.hu/api/publication/31276687},
	author = {Ayough, Ashkan and Zandieh, Mostafa and Farhadi, Farbod},
	doi = {10.1016/j.cie.2020.106363},
	journal-iso = {COMPUT IND ENG},
	journal = {COMPUTERS AND INDUSTRIAL ENGINEERING},
	volume = {143},
	unique-id = {31276687},
	issn = {0360-8352},
	year = {2020},
	eissn = {1879-0550},
	orcid-numbers = {Ayough, Ashkan/0000-0001-7706-2101; Zandieh, Mostafa/0000-0003-1209-9514}
}

@article{MTMT:31408624,
	title = {A Hybrid Unconscious Search Algorithm for Mixed-model Assembly Line Balancing Problem with SDST, Parallel Workstation and Learning Effect},
	url = {https://m2.mtmt.hu/api/publication/31408624},
	author = {Moein, Asadi-Zonouz and Majid, Khalili and Hamed, Tayebi},
	doi = {10.22094/JOIE.2020.579974.1605},
	journal-iso = {J OPTIM IN INDUST ENG},
	journal = {JOURNAL OF OPTIMIZATION IN INDUSTRIAL ENGINEERING},
	volume = {13},
	unique-id = {31408624},
	issn = {2251-9904},
	year = {2020},
	eissn = {2423-3935},
	pages = {123-140}
}

@article{MTMT:27503880,
	title = {Forming a cognitive automation strategy for Operator 4.0 in complex assembly},
	url = {https://m2.mtmt.hu/api/publication/27503880},
	author = {Sandra, Mattsson and Åsa, Fasth Berglund and Dan, Li and Peter, Thorvald},
	doi = {10.1016/j.cie.2018.08.011},
	journal-iso = {COMPUT IND ENG},
	journal = {COMPUTERS AND INDUSTRIAL ENGINEERING},
	volume = {139},
	unique-id = {27503880},
	issn = {0360-8352},
	year = {2020},
	eissn = {1879-0550}
}

@article{MTMT:30996694,
	title = {Application of Learning Curves in Operations Management Decisions},
	url = {https://m2.mtmt.hu/api/publication/30996694},
	author = {Tamás, Alexandra and Koltai, Tamás},
	doi = {10.3311/PPso.14136},
	journal-iso = {PERIOD POLYTECH SOC MANAG SCI},
	journal = {PERIODICA POLYTECHNICA SOCIAL AND MANAGEMENT SCIENCES},
	volume = {28},
	unique-id = {30996694},
	issn = {1416-3837},
	year = {2020},
	eissn = {1587-3803},
	pages = {81-90},
	orcid-numbers = {Koltai, Tamás/0000-0001-6873-6944}
}

@article{MTMT:30686691,
	title = {Batching decisions in multi-item production systems with learning effect},
	url = {https://m2.mtmt.hu/api/publication/30686691},
	author = {Castellano, Davide and Gallo, Mosè and Grassi, Andrea and Santillo, Liberatina C.},
	doi = {10.1016/j.cie.2018.12.068},
	journal-iso = {COMPUT IND ENG},
	journal = {COMPUTERS AND INDUSTRIAL ENGINEERING},
	volume = {131},
	unique-id = {30686691},
	issn = {0360-8352},
	year = {2019},
	eissn = {1879-0550},
	pages = {578-591},
	orcid-numbers = {Castellano, Davide/0000-0002-9023-0752}
}

@article{MTMT:31089147,
	title = {An innovative yield learning model considering multiple learning sources and learning source interactions},
	url = {https://m2.mtmt.hu/api/publication/31089147},
	author = {Chen, Tin-Chih Toly and Lin, Chi-Wei},
	doi = {10.1016/j.cie.2018.07.002},
	journal-iso = {COMPUT IND ENG},
	journal = {COMPUTERS AND INDUSTRIAL ENGINEERING},
	volume = {131},
	unique-id = {31089147},
	issn = {0360-8352},
	abstract = {Existing yield learning models do not separate the effects of different learning sources or consider the interactions among the sources. To address this problem, a multisource-with-interaction yield learning model was developed. In this paper, the properties of this multisource yield learning model are discussed from a theoretical and practical standpoint. In this study, the proposed methodology was applied to the manufacturing process of a dynamic random access memory product. The proposed model exhibited improved accuracy in estimating the future yield, evidencing its superiority over existing yield learning models. The proposed methodology can be generalized to model the learning processes of other performance measures in manufacturing or service systems.},
	keywords = {YIELD; Semiconductor; Interaction; artificial neural network; Learning source},
	year = {2019},
	eissn = {1879-0550},
	pages = {455-463}
}

@article{MTMT:30760382,
	title = {Approach to Reduce Throughput Time in Grinding of Gundrills},
	url = {https://m2.mtmt.hu/api/publication/30760382},
	author = {Mahesh, Vishwas and Shastry, Sudheendra and Murthy, Vasudev and Kumar, Vijay and Mahesh, Vinyas},
	doi = {10.18280/jesa.520204},
	journal-iso = {JOURNAL EUROPEEN DES SYSTEMES AUTOMATISES},
	journal = {JOURNAL EUROPEEN DES SYSTEMES AUTOMATISES},
	volume = {52},
	unique-id = {30760382},
	issn = {1269-6935},
	year = {2019},
	pages = {137-142}
}

@article{MTMT:27454037,
	title = {Solving the accessibility windows assembly line problem level 1 and variant 1 (AWALBP-L1-1) with precedence constraints},
	url = {https://m2.mtmt.hu/api/publication/27454037},
	author = {Alberto, García-Villoria and Albert, Corominas and Adrià, Nadal and Rafael, Pastor},
	doi = {10.1016/j.ejor.2018.05.048},
	journal-iso = {EJOR},
	journal = {EUROPEAN JOURNAL OF OPERATIONAL RESEARCH},
	volume = {271},
	unique-id = {27454037},
	issn = {0377-2217},
	year = {2018},
	eissn = {1872-6860},
	pages = {882-895}
}

@article{MTMT:30374983,
	title = {MONTAJ HATLARINDA YENİDEN İŞLEME İSTASYON POZİSYONUNUN OPTİMİZASYONU İÇİN BİR KARIŞIK-TAMSAYILI PROGRAMLAMA MODELİ},
	url = {https://m2.mtmt.hu/api/publication/30374983},
	author = {ÇAVDUR, Fatih and KAYMAZ, Elif and SEBATLI, Aslı},
	doi = {10.17482/uumfd.420001},
	journal-iso = {ULUDAG UNIV J FACULT ENGIN},
	journal = {ULUDAG ÜNIVERSITESI MÜHENDISLIK FAKÜLTESI DERGISI / ULUDAG UNIVERSITY JOURNAL OF THE FACULTY OF ENGINEERING},
	volume = {23},
	unique-id = {30374983},
	issn = {2148-4147},
	year = {2018},
	eissn = {2148-4155},
	pages = {273-288}
}