Добірка наукової літератури з теми "Unbalanced optimal transportation"
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Статті в журналах з теми "Unbalanced optimal transportation"
Nopiyana, P. Affandi, and A. S. Lestia. "Solving transportation problem using modified ASM method." Journal of Physics: Conference Series 2106, no. 1 (November 1, 2021): 012029. http://dx.doi.org/10.1088/1742-6596/2106/1/012029.
Повний текст джерелаJoshi, Nidhi, and Surjeet Singh Chauhan. "A new Approach for Obtaining Optimal Solution of Unbalanced Fuzzy Transportation Problem." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 15, no. 6 (April 20, 2016): 6824–32. http://dx.doi.org/10.24297/ijct.v15i6.3977.
Повний текст джерелаKumar, Amit, and Amarpreet Kaur. "Methods for Solving Fully Fuzzy Transportation Problems Based on Classical Transportation Methods." International Journal of Operations Research and Information Systems 2, no. 4 (October 2011): 52–71. http://dx.doi.org/10.4018/joris.2011100104.
Повний текст джерелаProkudin, Georgii, Alexey Chupaylenko, Tetiana Khobotnia, Inna Remekh, Andrei Lyamzin, and Marina Kovalenko. "Optimizing unbalanced freight deliveries in transportation networks." Eastern-European Journal of Enterprise Technologies 2, no. 3 (116) (April 28, 2022): 22–32. http://dx.doi.org/10.15587/1729-4061.2022.253791.
Повний текст джерелаHamoud, Ahmed, Kirtiwant Ghadle, and Priyanka Pathade. "DA systematic approach for solving mixed constraint fuzzy balanced and unbalanced transportation problem." Indonesian Journal of Electrical Engineering and Computer Science 19, no. 1 (July 1, 2020): 85. http://dx.doi.org/10.11591/ijeecs.v19.i1.pp85-90.
Повний текст джерелаSrinivasan, N., and A. Seethalakshmy. "A Heuristic Approach to Obtain an Optimal Solution for Unbalanced Transportation Problem." International Journal of Engineering & Technology 7, no. 4.10 (October 2, 2018): 364. http://dx.doi.org/10.14419/ijet.v7i4.10.20936.
Повний текст джерелаGhadle, Kirtiwant P., and Priyanka A. Pathade. "Optimal Solution of Balanced and Unbalanced Fuzzy Transportation Problem Using Hexagonal Fuzzy Numbers." International Journal of Mathematical Research 5, no. 2 (2016): 131–37. http://dx.doi.org/10.18488/journal.24/2016.5.2/24.2.131.137.
Повний текст джерелаBisht, Dinesh C. S., and Pankaj Kumar Srivastava. "One Point Conventional Model to Optimize Trapezoidal Fuzzy Transportation Problem." International Journal of Mathematical, Engineering and Management Sciences 4, no. 5 (October 1, 2019): 1251–63. http://dx.doi.org/10.33889/ijmems.2019.4.5-099.
Повний текст джерелаAdhikari, Purnima, and Gyan Bahadur Thapa. "A Note on Feasibility and Optimality of Transportation Problem." Journal of the Institute of Engineering 10, no. 1 (July 31, 2014): 59–68. http://dx.doi.org/10.3126/jie.v10i1.10879.
Повний текст джерелаGupta, Anila, Amit Kumar, and Amarpreet Kaur. "Mehar’s method to find exact fuzzy optimal solution of unbalanced fully fuzzy multi-objective transportation problems." Optimization Letters 6, no. 8 (July 20, 2011): 1737–51. http://dx.doi.org/10.1007/s11590-011-0367-2.
Повний текст джерелаДисертації з теми "Unbalanced optimal transportation"
Гайдук, Ірина Вадимівна. "Вирішення транспортної задачі методами машинного навчання". Master's thesis, КПІ ім. Ігоря Сікорського, 2021. https://ela.kpi.ua/handle/123456789/46504.
Повний текст джерелаMaster’s thesis: 87 pages, 27 figures, 24 tables, 21 sources. Theme: The classical problem of optimal transportation. The conducted research solves it by known methods, their advantages and disadvantages, the necessary conditions for the existence of an optimal solution. This was a proposed machine method for solving problems with the construction and model of learning based on a generative neural network. The paper considered general information on the method of solving the problem of optimal transportation with its unbalance and scalability. The results of three different types of problems solved by the machine learning method were analyzed. The subject of the study is the classical problem of optimal transportation in three different types. The subject of research is the methods of machine learning, in particular the generative competitive neural network.
Частини книг з теми "Unbalanced optimal transportation"
Kumar, P. Senthil. "Finding the Solution of Balanced and Unbalanced Intuitionistic Fuzzy Transportation Problems by Using Different Methods With Some Software Packages." In Advances in Marketing, Customer Relationship Management, and E-Services, 278–320. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-5077-9.ch015.
Повний текст джерелаТези доповідей конференцій з теми "Unbalanced optimal transportation"
Chen, Yimeng, Yanyan Lan, Ruinbin Xiong, Liang Pang, Zhiming Ma, and Xueqi Cheng. "Evaluating Natural Language Generation via Unbalanced Optimal Transport." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/516.
Повний текст джерелаReddy, Moupuri Satish Kumar, Asisa Kumar Panigrahy, and K. Selvajyothi. "Minimization of Electric Vehicle charging Stations influence on Unbalanced radial distribution system with Optimal Reconfiguration using Particle Swarm Optimization." In 2021 International Conference on Sustainable Energy and Future Electric Transportation (SEFET). IEEE, 2021. http://dx.doi.org/10.1109/sefet48154.2021.9375665.
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