Relevant bibliographies by topics / Unbalanced optimal transportation

Academic literature on the topic 'Unbalanced optimal transportation'

Author: Grafiati
Published: 30 May 2022
Last updated: 31 May 2022

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Journal articles on the topic "Unbalanced optimal transportation"

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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.

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Abstract Transportation problems are related to activities aimed at minimizing the cost of distributing goods from a source to a destination. One of the methods used to solve transportation problems is the ASM Method as a method capable of producing optimal direct solutions without having to determine the initial basic feasible solution first. Determination of the allocation of goods in the ASM Method uses a reduced cost of 0 by calculating the maximum amount in the allocation of goods. Then the ASM method is modified so that the iteration used is simpler in obtaining the optimal direct solution without calculating the maximum number of row and column elements. The method is called Modified ASM Method. This method also provides more optimal results than the ASM method. This research aimed to solve transportation problems using the Modified ASM method to produce optimal solutions directly. The research procedure identifies and forms a model of transportation problems (variable decisions, objective functions and constraint functions), identifies types of transportation problems (balanced or unbalanced), and obtains direct solutions by solving transportation problems using the Modified ASM method. This research shows that the Modified ASM method successfully solves the problem of balanced and unbalanced transportation by producing optimal solutions in a simpler way than the ASM method.
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Joshi, 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.

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The present paper attempts to study the unbalanced fuzzy transportation problem so as to minimize the transportationcost of products when supply, demand and cost of the products are represented by fuzzy numbers. In this paper, authorsuse Roubast ranking technique to transform trapezoidal fuzzy numbers to crisp numbers and propose a new algorithm tofind the fuzzy optimal solution of unbalanced fuzzy transportation problem. The proposed algorithm is more efficient thanother existing algorithms like simple VAM and is illustrated via numerical example. Also, a comparison between the resultsof the new algorithm and the result of algorithm using simple VAM is provided.
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Kumar, 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.

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There are several methods, in literature, for finding the fuzzy optimal solution of fully fuzzy transportation problems (transportation problems in which all the parameters are represented by fuzzy numbers). In this paper, the shortcomings of some existing methods are pointed out and to overcome these shortcomings, two new methods (based on fuzzy linear programming formulation and classical transportation methods) are proposed to find the fuzzy optimal solution of unbalanced fuzzy transportation problems by representing all the parameters as trapezoidal fuzzy numbers. The advantages of the proposed methods over existing methods are also discussed. To illustrate the proposed methods a fuzzy transportation problem (FTP) is solved by using the proposed methods and the obtained results are discussed. The proposed methods are easy to understand and to apply for finding the fuzzy optimal solution of fuzzy transportation problems occurring in real life situations.
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Prokudin, 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.

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This paper reports a comparative analysis of the known methods for reducing open transportation problems to a balanced form in order to further optimize freight traffic based on them. A series of significant shortcomings have been revealed that largely narrow the scope of their application. A new method has been proposed, termed the method of proportional redistribution of cargo transportation volumes among participants in the transportation process, devoid of the identified shortcomings. The transportation problem is a special case of the general linear programming problem, to which one of the methods for solving it, namely the simplex one, can be applied. A procedure to construct a simplex table based on the data from the transport table has been described, as well as the algorithm of subsequent simplex transformations. A transportation problem is often stated in the form of a map of the location of transport hubs of cargo dispatch and destination. A matrix-network model has been proposed, which makes it possible to reduce the network representation to a matrix form with the subsequent finding of the optimal plan for cargo transportation. In order to identify the priority of methods for reducing open transportation problems to a balanced form, 100 transportation problems that are unbalanced in terms of the volume of cargo transportation were solved. That was done with the help of a designed decision support system for the management of freight transport. As a criterion, the best freight transportation plan was chosen. As a result, the simplex method proved the best in 48 cases, the coefficient method ‒ in 27, the dummy node method ‒ in 16, and the difference method ‒ in 9 cases. The use of a decision support system for the management of freight transport has increased its efficiency by an average of 25 %
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Hamoud, 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.

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<p>In the present article, a mixed type transportation problem is considered. Most of the transportation problems in real life situation have mixed type transportation problem this type of transportation problem cannot be solved by usual methods. Here we attempt a new concept of Best Candidate Method (BCM) to obtain the optimal solution. To determine the compromise solution of balanced mixed fuzzy transportation problem and unbalanced mixed fuzzy transportation problem of trapezoidal and trivial fuzzy numbers with new BCM solution procedure has been applied. The method is illustrated by the numerical examples.</p>
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Srinivasan, 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.

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This Method is proposed for obtaining an optimal solution for transportation problem. This method gives the optimal solution in lesser iteration. Here find the difference between two consecutive maximum for row-wise and column-wise. In that find the maximum value, for which the minimum is allocated by the minimum supply or demand. Illustration for this method is given with some examples at the end.
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Ghadle, 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.

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Bisht, 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.

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This article puts forward a new one point approach to optimize trapezoidal fuzzy transportation problem. It proposes the method having point wise breakup of the trapezoidal number in such a way, that fuzzy transportation problem is converted into four crisp transportation problems. The method is equipped with minimum of supply and demand approach. In the end, the solutions are combined to construct the optimal solution. Modified distribution is applied on each crisp problem to develop optimal solution. The scheme presented is compared with competitive methods available in literature and it is found to be in good coordination with these. The scheme is equally good to be applied on unbalanced problems. Two numerical problems are considered to test the performance of the proposed approach.
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Adhikari, 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.

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Transportation problem is one of the predominant areas of operations research, widely used as a decision making tool in engineering, business management and many other fields. In this paper, we present a brief literature review of transportation problem with its mathematical models in balanced and unbalanced cases. We report the basic feasible solution and hence the methods to attain optimal solution of the balanced transportation problem. Finally, we describe the primal-dual case of the problem with counter examples. DOI: http://dx.doi.org/10.3126/jie.v10i1.10879Journal of the Institute of Engineering, Vol. 10, No. 1, 2014, pp. 59–68
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Gupta, 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.

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Dissertations / Theses on the topic "Unbalanced optimal transportation"

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Гайдук, Ірина Вадимівна. "Вирішення транспортної задачі методами машинного навчання." Master's thesis, КПІ ім. Ігоря Сікорського, 2021. https://ela.kpi.ua/handle/123456789/46504.

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Магістерська дисертація: 87 с., 27 рисунків, 24 таблиці, 21 джерело. В роботі розглянута класична задача оптимального транспортування. Проведено дослідження відомих методів її вирішення, їх переваги та недоліки, необхідні умови існування оптимального розв’язку. Окрім цього, був запропонований машинний метод вирішення задачі з побудовою та навчанням моделі на основі генеративної нейронної мережі. В роботі було розглянуто загальні відомості про методи вирішення задачі оптимального транспортування при її незбалансованості та масштабованості. Було виконано аналіз результатів трьох різних типів задач, вирішених методом машинного навчання. Об’єктом дослідження є класична задача оптимального транспортування у трьох різних видах. Предметом дослідження є методи машинного навчання, зокрема генеративна змагальна нейронна мережа.
Master’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.
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Book chapters on the topic "Unbalanced optimal transportation"

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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.

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In this chapter, two different methodologies are proposed to find out the optimal solution to the balanced and unbalanced intuitionistic fuzzy transportation problems (UBIFTPs). In addition, the parameter of both the balanced and UBIFTPs are considered to be triangular intuitionistic fuzzy numbers (TIFNs). Two new methodologies, respectively method-1 and method-2, are presented in this chapter. Proposed method-1 is based on linear programming technique, and proposed method-2 is based on modified distribution method. Both the methodologies are used to solve the balanced and UBIFTPs. The ideas of the proposed methodologies are illustrated with the help of real-life numerical examples. The solutions obtained by the proposed methodologies are checked with some software (e.g., MATLAB, LINGO) and the computer code related to the proposed problems is also given. The unique results, comparative study, discussions, and the merits of the proposed methodologies are all given. At the end of the chapter, future work is mentioned.
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Conference papers on the topic "Unbalanced optimal transportation"

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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.

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Embedding-based evaluation measures have shown promising improvements on the correlation with human judgments in natural language generation. In these measures, various intrinsic metrics are used in the computation, including generalized precision, recall, F-score and the earth mover's distance. However, the relations between these metrics are unclear, making it difficult to determine which measure to use in real applications. In this paper, we provide an in-depth study on the relations between these metrics. Inspired by the optimal transportation theory, we prove that these metrics correspond to the optimal transport problem with different hard marginal constraints. However, these hard marginal constraints may cause the problem of incomplete and noisy matching in the evaluation process. Therefore we propose a family of new evaluation metrics, namely Lazy Earth Mover's Distances, based on the more general unbalanced optimal transport problem. Experimental results on WMT18 and WMT19 show that our proposed metrics have the ability to produce more consistent evaluation results with human judgements, as compared with existing intrinsic metrics.
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Reddy, 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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