https://orcid.org/0000-0002-0502-113X
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Yuhan Guo, Wenhua Li, Linfan Xiao & Hamid Allaoui. (2024) A prediction-based iterative Kuhn-Munkres approach for service vehicle reallocation in ride-hailing. International Journal of Production Research 62:10, pages 3690-3715.
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Bingxin Miao, Qianwang Deng, Like Zhang, Zhangwen Huo & Weifeng Han. (2024) Joint scheduling of spare parts production and service engineers based on progressive Pareto algorithm. International Journal of Production Research 62:6, pages 2124-2141.
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Kamal Sanguri, Sabyasachi Patra, Konstantinos Nikolopoulos & Sushil Punia. (2024) Intermittent demand, inventory obsolescence, and temporal aggregation forecasts. International Journal of Production Research 62:5, pages 1663-1685.
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Li Li, Yanfei Kang, Fotios Petropoulos & Feng Li. (2023) Feature-based intermittent demand forecast combinations: accuracy and inventory implications. International Journal of Production Research 61:22, pages 7557-7572.
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Vahid Babaveisi, Ebrahim Teimoury, Mohammad Reza Gholamian & Bahman Rostami-Tabar. (2023) Integrated demand forecasting and planning model for repairable spare part: an empirical investigation. International Journal of Production Research 61:20, pages 6791-6807.
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Emna Turki, Oualid Jouini, Zied Jemai, Yazid Traiy, Adnane Lazrak, Patrick Valot & Robert Heidseick. Forecasting spare part extractions from returned systems in a closed-loop supply chain. International Journal of Production Research 0:0, pages 1-17.
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Marwa Hasni, M. Zied Babai & Bahman Rostami-Tabar. A hybrid LSTM method for forecasting demands of medical items in humanitarian operations. International Journal of Production Research 0:0, pages 1-18.
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Articles from other publishers (17)
Shengjie Wang, Yanfei Kang & Fotios Petropoulos. (2024) Combining probabilistic forecasts of intermittent demand. European Journal of Operational Research 315:3, pages 1038-1048.
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Corey Ducharme, Bruno Agard & Martin Trépanier. (2024) Improving demand forecasting for customers with missing downstream data in intermittent demand supply chains with supervised multivariate clustering. Journal of Forecasting.
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Zhiqiang Cui, Hongli Jia, Qi Gao & Haowen Song. (2024) Maintenance Spare Parts Prediction Based on Multilevel Migration Learning CNN-ISE-Attention-BiLSTM. IEEE Access 12, pages 15208-15221.
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Yashar Ahmadov & Petri Helo. (2023) Deep learning-based approach for forecasting intermittent online sales. Discover Artificial Intelligence 3:1.
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Shuyi Sun & Peng Jiang. (2023) Multi-Task Least-Squares Support Vector Regression Model for Predicting Co-Abundance of Antibiotic Resistance Genes and Resistant Bacteria. Multi-Task Least-Squares Support Vector Regression Model for Predicting Co-Abundance of Antibiotic Resistance Genes and Resistant Bacteria.
Ayda Amniattalab, J.B.G. Frenk & Mustafa Hekimoğlu. (2023) On spare parts demand and the installed base concept: A theoretical approach. International Journal of Production Economics 266, pages 109043.
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Milton Soto-Ferrari, Kuntal Bhattacharyya & Paul Schikora. (2023) POST-BaLSTM: A Bagged LSTM forecasting ensemble embedded with a postponement framework to target the semiconductor shortage in the automotive industry. Computers & Industrial Engineering 185, pages 109602.
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Saba Sareminia. (2022) A Support Vector Based Hybrid Forecasting Model for Chaotic Time Series: Spare Part Consumption Prediction. Neural Processing Letters 55:3, pages 2825-2841.
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Kamal Sanguri, Sabyasachi Patra & Sushil Punia. (2023) Forecast reconciliation in the temporal hierarchy: Special case of intermittent demand with obsolescence. Expert Systems with Applications 218, pages 119566.
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Ferhat Yuna, Burak Erkayman & Mustafa Yılmaz. (2023) Inventory control model for intermittent demand: a comparison of metaheuristics. Soft Computing 27:10, pages 6487-6505.
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Imran Shafi, Amir Sohail, Jamil Ahmad, Julio César Martínez Espinosa, Luis Alonso Dzul López, Ernesto Bautista Thompson & Imran Ashraf. (2023) Spare Parts Forecasting and Lumpiness Classification Using Neural Network Model and Its Impact on Aviation Safety. Applied Sciences 13:9, pages 5475.
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Harsora Karn & Ajay Gupta. 2023. Applications of Emerging Technologies and AI/ML Algorithms. Applications of Emerging Technologies and AI/ML Algorithms
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Dennis Prak & Patricia Rogetzer. (2022) Timing intermittent demand with time-varying order-up-to levels. European Journal of Operational Research 303:3, pages 1126-1136.
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Ferhat YUNA & Burak ERKAYMAN. (2022) A Genetic Algorithm-Based Model for Inventory Control in Intermittent Demands. European Journal of Science and Technology.
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Xiaolin Chu & Ruijuan Zhao. (2021) A building carbon emission prediction model by PSO-SVR method under multi-criteria evaluation. Journal of Intelligent & Fuzzy Systems 41:6, pages 7473-7484.
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Joaquim Tinoco, António Alberto S. Correia & Paulo J. Venda Oliveira. (2021) Soil-Cement Mixtures Reinforced with Fibers: A Data-Driven Approach for Mechanical Properties Prediction. Applied Sciences 11:17, pages 8099.
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Khurram Rehmani, Afshan Naseem, Yasir Ahmad, Muhammad Zeeshan Mirza & Tasweer Hussain Syed. (2021) Development of a hybrid framework for inventory leanness in Technical Services Organizations. PLOS ONE 16:2, pages e0247144.
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