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Liukai Wang, Xinyi Kong, Weiqing Wang & Yu Gong. (2024) Pursuing supply chain ecosystem health under environmental turbulence: a supply chain learning approach. International Journal of Production Research 62:8, pages 2792-2811.
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Benjamin Rolf, Ilya Jackson, Marcel Müller, Sebastian Lang, Tobias Reggelin & Dmitry Ivanov. (2023) A review on reinforcement learning algorithms and applications in supply chain management. International Journal of Production Research 61:20, pages 7151-7179.
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Ana Esteso, David Peidro, Josefa Mula & Manuel Díaz-Madroñero. (2023) Reinforcement learning applied to production planning and control. International Journal of Production Research 61:16, pages 5772-5789.
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Lotte van Hezewijk, Nico Dellaert, Tom Van Woensel & Noud Gademann. (2023) Using the proximal policy optimisation algorithm for solving the stochastic capacitated lot sizing problem. International Journal of Production Research 61:6, pages 1955-1978.
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Thomas Gabel & Martin Riedmiller. (2012) Distributed policy search reinforcement learning for job-shop scheduling tasks. International Journal of Production Research 50:1, pages 41-61.
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Peide Liu & Xin Zhang. (2011) Research on the supplier selection of a supply chain based on entropy weight and improved ELECTRE-III method. International Journal of Production Research 49:3, pages 637-646.
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Hing K. Chan & Felix T.S. Chan. (2010) A review of coordination studies in the context of supply chain dynamics. International Journal of Production Research 48:10, pages 2793-2819.
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S Liu & RIM Young. (2004) Utilizing information and knowledge models to support global manufacturing co-ordination decisions. International Journal of Computer Integrated Manufacturing 17:6, pages 479-492.
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Youssra Riahi, Tarik Saikouk, Ismail Badraoui & Samuel Fosso Wamba. Researched topics, patterns, barriers and enablers of artificial intelligence implementation in supply chain: a Latent-Dirichlet-allocation-based topic-modelling and expert validation. Production Planning & Control 0:0, pages 1-28.
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Articles from other publishers (49)
Sabah Bushaj & İ. Esra Büyüktahtakın. (2024) A K-means Supported Reinforcement Learning Framework to Multi-dimensional Knapsack. Journal of Global Optimization.
Crossref
Crossref
Jayeeta Mondal, Jeet Dutta & Hrishav Bakul Barua. 2023. Advanced AI and Internet of Health Things for Combating Pandemics. Advanced AI and Internet of Health Things for Combating Pandemics
337
358
.
Mohamed Kriouich, Hicham Sarir & Oussama Mahboub. 2023. Proceedings of the 6th International Conference on Big Data and Internet of Things. Proceedings of the 6th International Conference on Big Data and Internet of Things
388
401
.
Manoj Shakya, Bu-Sung Lee & Huey Yuen Ng. (2022) A Deep Reinforcement Learning Approach for Inventory Control under Stochastic Lead Time and Demand. A Deep Reinforcement Learning Approach for Inventory Control under Stochastic Lead Time and Demand.
Dony S. Kurian, V. Madhusudanan Pillai, Akash Raut & J. Gautham. (2022) Deep reinforcement learning‐based ordering mechanism for performance optimization in multi‐echelon supply chains. Applied Stochastic Models in Business and Industry.
Crossref
Crossref
Yimo Yan, Andy H.F. Chow, Chin Pang Ho, Yong-Hong Kuo, Qihao Wu & Chengshuo Ying. (2022) Reinforcement learning for logistics and supply chain management: Methodologies, state of the art, and future opportunities. Transportation Research Part E: Logistics and Transportation Review 162, pages 102712.
Crossref
Crossref
Qiang Zhou, Yefei Yang & Shaochuan Fu. (2022) Deep reinforcement learning approach for solving joint pricing and inventory problem with reference price effects. Expert Systems with Applications 195, pages 116564.
Crossref
Crossref
Manoj Shakya, Huey Yuen Ng, Darrell Joshua Ong & Bu-Sung Lee. 2022. Artificial Intelligence Applications and Innovations. Artificial Intelligence Applications and Innovations
282
291
.
Swetha Govindaiah & Mikel D. Petty. (2021) Applying reinforcement learning to plan manufacturing material handling. Discover Artificial Intelligence 1:1.
Crossref
Crossref
Mehrdokht Pournader, Hadi Ghaderi, Amir Hassanzadegan & Behnam Fahimnia. (2021) Artificial intelligence applications in supply chain management. International Journal of Production Economics 241, pages 108250.
Crossref
Crossref
Apoorva Gokhale, Chirag Trasikar, Ankit Shah, Arpita Hegde & Sowmiya Raksha Naik. 2021. Advances in Artificial Intelligence and Data Engineering. Advances in Artificial Intelligence and Data Engineering
281
297
.
Yassine Hachaichi, Yassine Chemingui & Mariem Affes. (2020) A Policy Gradient Based Reinforcement Learning Method for Supply Chain Management. A Policy Gradient Based Reinforcement Learning Method for Supply Chain Management.
Leonardo Espinosa-Leal, Anthony Chapman & Magnus Westerlund. (2020) Autonomous Industrial Management via Reinforcement Learning. Journal of Intelligent & Fuzzy Systems 39:6, pages 8427-8439.
Crossref
Crossref
Eszter Puskás, Ádám Budai & Gábor Bohács. (2020) Optimization of a physical internet based supply chain using reinforcement learning. European Transport Research Review 12:1.
Crossref
Crossref
Michele Compare, Luca Bellani, Enrico Cobelli, Enrico Zio, Francesco Annunziata, Fausto Carlevaro & Marzia Sepe. (2019) A reinforcement learning approach to optimal part flow management for gas turbine maintenance. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 234:1, pages 52-62.
Crossref
Crossref
Shraddha Bharti, Dony S. Kurian & V. Madhusudanan Pillai. 2020. Innovative Product Design and Intelligent Manufacturing Systems. Innovative Product Design and Intelligent Manufacturing Systems
877
885
.
Esha Saha & Pradip Kumar Ray. (2019) Modelling and analysis of inventory management systems in healthcare: A review and reflections. Computers & Industrial Engineering 137, pages 106051.
Crossref
Crossref
Ryan J. Lawhead & Abhijit Gosavi. (2019) A bounded actor–critic reinforcement learning algorithm applied to airline revenue management. Engineering Applications of Artificial Intelligence 82, pages 252-262.
Crossref
Crossref
Shraddha Mishra, Surya Prakash Singh, John Johansen, Yang Cheng & Sami Farooq. (2019) Evaluating indicators for international manufacturing network under circular economy. Management Decision 57:4, pages 811-839.
Crossref
Crossref
Michele Compare, Luca Bellani, Enrico Cobelli & Enrico Zio. (2018) Reinforcement learning-based flow management of gas turbine parts under stochastic failures. The International Journal of Advanced Manufacturing Technology 99:9-12, pages 2981-2992.
Crossref
Crossref
Markus Rabe & Felix Dross. (2015) A Reinforcement Learning approach for a Decision Support System for logistics networks. A Reinforcement Learning approach for a Decision Support System for logistics networks.
Hadiyan Wijaya Ibrahim, Suhaiza Zailani & Keah Choon Tan. (2015) A content analysis of global supply chain research. Benchmarking: An International Journal 22:7, pages 1429-1462.
Crossref
Crossref
Ion Matei, Assane Gueye & John S. Baras. (2015) Flow control in time-varying, random supply chains. Transportation Research Part E: Logistics and Transportation Review 77, pages 311-330.
Crossref
Crossref
Ahmad Mortazavi, Alireza Arshadi Khamseh & Parham Azimi. (2015) Designing of an intelligent self-adaptive model for supply chain ordering management system. Engineering Applications of Artificial Intelligence 37, pages 207-220.
Crossref
Crossref
Christopher GattiChristopher Gatti. 2015. Design of Experiments for Reinforcement Learning. Design of Experiments for Reinforcement Learning
7
52
.
Abhijit GosaviAbhijit Gosavi. 2015. Simulation-Based Optimization. Simulation-Based Optimization
451
471
.
Miguel González-Loureiro, Marina Dabic & Francisco Puig. (2014) Global organizations and supply chain. International Journal of Physical Distribution & Logistics Management 44:8/9, pages 689-712.
Crossref
Crossref
Jahani Alireza, Azmi Murad Masrah Azrifah, Sulaiman Nasir & Selamat Hasan. (2013) A Multi-Agent Supply Chain Recommendation and Negotiation Framework. Advanced Materials Research 716, pages 527-532.
Crossref
Crossref
Carlos R. Jaimez-Gonzalez & Wulfrano A. Luna-Ramirez. (2013) An agent-based architecture for supply chain management. An agent-based architecture for supply chain management.
Seyed-Mahmoud Aghazadeh. 2013. Supply Chain Management. Supply Chain Management
1626
1636
.
Seyed-Mahmoud Aghazadeh. 2013. Outsourcing Management for Supply Chain Operations and Logistics Service. Outsourcing Management for Supply Chain Operations and Logistics Service
466
476
.
Arpita Khare & Anshuman Khare. (2012) Harnessing Supply Chain Efficiency Through Information Linkages. International Journal of Information Systems and Supply Chain Management 5:4, pages 86-104.
Crossref
Crossref
Hans-Jörg Schütz & Rainer Kolisch. (2012) Approximate dynamic programming for capacity allocation in the service industry. European Journal of Operational Research 218:1, pages 239-250.
Crossref
Crossref
Tatpong Katanyukul, William S. Duff & Edwin K.P. Chong. (2011) Approximate dynamic programming for an inventory problem: Empirical comparison. Computers & Industrial Engineering 60:4, pages 719-743.
Crossref
Crossref
Ingo J. Timm & Andreas D. Lattner. (2010) Künstliche Intelligenz in der Logistik. KI - Künstliche Intelligenz 24:2, pages 99-103.
Crossref
Crossref
Jiancheng Guan & Lei Fan. 2010. Advances in Intelligent Decision Technologies. Advances in Intelligent Decision Technologies
259
267
.
Bernard Grabot, Stefan Marsina, Anne Mayère, Ralph Riedel & Peter Williams. 2011. Behavioral Operations in Planning and Scheduling. Behavioral Operations in Planning and Scheduling
123
158
.
H. Ding, W. Wang, M. Qiu & J. Dong. 2010. Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management. Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management
87
105
.
Abhijit Gosavi. (2009) Reinforcement Learning: A Tutorial Survey and Recent Advances. INFORMS Journal on Computing 21:2, pages 178-192.
Crossref
Crossref
Wang Xiao-Gang & Li Yue. (2009) A Method of Collaborative Negotiation for Supply Chain Coordination. A Method of Collaborative Negotiation for Supply Chain Coordination.
Xiao-Gang Wang, Gang Liu & Yue Li. (2009) A Strategy of Collaborative Negotiation for Dynamic Supply Chain Coordination. A Strategy of Collaborative Negotiation for Dynamic Supply Chain Coordination.
Xiao-Gang Wang, Gang Liu & Yue Li. (2009) A Strategy of Collaborative Negotiation for Dynamic Supply Chain Coordination. A Strategy of Collaborative Negotiation for Dynamic Supply Chain Coordination.
Sunil Babbar, Helena Addae, Jerry Gosen & Sameer Prasad. (2008) Organizational factors affecting supply chains in developing countries. International Journal of Commerce and Management 18:3, pages 234-251.
Crossref
Crossref
A A Afify, S S Dimov, M Naim, V Valeva & V Shukla. (2007) Data mining: A tool for detecting cyclical disturbances in supply networks. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 221:12, pages 1771-1785.
Crossref
Crossref
Jianxin (Roger) Jiao, Xiao You & Arun Kumar. (2006) An agent-based framework for collaborative negotiation in the global manufacturing supply chain network. Robotics and Computer-Integrated Manufacturing 22:3, pages 239-255.
Crossref
Crossref
Hengshuai Yao, Diao Dongcui & Zengqi Sun. (2006) Historical Temporal Difference Learning: Some Initial Results. Historical Temporal Difference Learning: Some Initial Results.
C.O. Kim, J. Jun, J.K. Baek, R.L. Smith & Y.D. Kim. (2004) Adaptive inventory control models for supply chain management. The International Journal of Advanced Manufacturing Technology 26:9-10, pages 1184-1192.
Crossref
Crossref
J. Jiao, X. You & Arun Kumar. (2005) Agent-based collaborative negotiation for manufacturing supply chain coordination. Agent-based collaborative negotiation for manufacturing supply chain coordination.
Yimo Yan, Andy H.F. Chow, Chin Pang Ho, Yong-Hong Kuo, Qihao Wu & Chengshuo Ying. (2021) Reinforcement Learning for Logistics and Supply Chain Management: Methodologies, State of the Art, and Future Opportunities. SSRN Electronic Journal.
Crossref
Crossref