Literatura académica sobre el tema "Bi-Criteria decision making"
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Artículos de revistas sobre el tema "Bi-Criteria decision making"
Dahong, Tang y Chen Ting. "Multi-criteria Decision Making Problems with Bi-level Multiagent". IFAC Proceedings Volumes 22, n.º 10 (agosto de 1989): 275–79. http://dx.doi.org/10.1016/s1474-6670(17)53185-7.
Texto completoFazlollahtabar, Hamed, Ermia Aghasi y Peter Forte. "Bi-Objective Two-Stage Decision-Making Process for Service Marketing". International Journal of Strategic Decision Sciences 3, n.º 3 (julio de 2012): 24–39. http://dx.doi.org/10.4018/jsds.2012070103.
Texto completoZhang, Ling, Yan Xu, Chung-Hsing Yeh, Le He y De-Qun Zhou. "Bi-TOPSIS: A New Multicriteria Decision Making Method for Interrelated Criteria With Bipolar Measurement". IEEE Transactions on Systems, Man, and Cybernetics: Systems 47, n.º 12 (diciembre de 2017): 3272–83. http://dx.doi.org/10.1109/tsmc.2016.2573582.
Texto completoMalakooti, Behnam. "Double Helix Value Functions, Ordinal/Cardinal Approach, Additive Utility Functions, Multiple Criteria, Decision Paradigm, Process, and Types (Z Theory I)". International Journal of Information Technology & Decision Making 14, n.º 06 (noviembre de 2015): 1353–400. http://dx.doi.org/10.1142/s0219622014500412.
Texto completoHuang, Deng Kui, Huan Neng Chiu, Ruey Huei Yeh y Jen Huei Chang. "A fuzzy multi-criteria decision making approach for solving a bi-objective personnel assignment problem". Computers & Industrial Engineering 56, n.º 1 (febrero de 2009): 1–10. http://dx.doi.org/10.1016/j.cie.2008.03.007.
Texto completoABO-SINNA, MAHMOUD A. y AZZA H. AMER. "TOPSIS Approach for Solving Bi-Level Non-Linear Fractional MODM Problems". JOURNAL OF ADVANCES IN MATHEMATICS 13, n.º 4 (9 de febrero de 2018): 7353–70. http://dx.doi.org/10.24297/jam.v13i4.6243.
Texto completoGhazanfari, Mehdi, Saeed Rouhani y Mostafa Jafari. "A fuzzy TOPSIS model to evaluate the Business Intelligence competencies of Port Community Systems". Polish Maritime Research 21, n.º 2 (1 de abril de 2014): 86–96. http://dx.doi.org/10.2478/pomr-2014-0023.
Texto completoAraz, Ozgur M., Tim Lant, John W. Fowler y Megan Jehn. "Simulation modeling for pandemic decision making: A case study with bi-criteria analysis on school closures". Decision Support Systems 55, n.º 2 (mayo de 2013): 564–75. http://dx.doi.org/10.1016/j.dss.2012.10.013.
Texto completoGadomski, Jan y Lech Kruś. "Objectives of an enterprise. Bi-criteria analysis and negotiation problems". Control and Cybernetics 50, n.º 1 (1 de marzo de 2021): 169–93. http://dx.doi.org/10.2478/candc-2021-0010.
Texto completoKrivulin, Nikolai. "Algebraic Solution to Constrained Bi-Criteria Decision Problem of Rating Alternatives through Pairwise Comparisons". Mathematics 9, n.º 4 (4 de febrero de 2021): 303. http://dx.doi.org/10.3390/math9040303.
Texto completoTesis sobre el tema "Bi-Criteria decision making"
Nguyen, Minh Hieu. "Bi-objective optimization with proportional fairness". Electronic Thesis or Diss., Université Clermont Auvergne (2021-...), 2024. http://www.theses.fr/2024UCFA0036.
Texto completoBi-Objective Combinatorial Optimization (BOCO) is a type of multiple-criteria decision-making with many applications in different scientific areas, such as economics, supply chain, telecommunications, computer science, and social choice. It involves optimizing simultaneously two (conflict) objective functions in a finite feasible set of decision vectors. For BOCO, the concept of Pareto-optimal (non-dominated) solution plays an important role as it distinguishes between efficient and non-efficient solutions. Based on this concept, popular methods for solving BOCO usually construct a representation of the Pareto set that represents different trade-offs between the objectives. Proportional fairness is a widely studied concept in the literature that aims to distribute utilities to ensure fairness and equity among users while optimizing system performance. Related to the proportional changes, it can be used as a standard comparison for two solutions of BOCO, even when the two objectives have different orders of magnitude. The goal of this thesis is to propose a novel criterion for selecting preferred Pareto-optimal solutions in the Pareto set of a general BOCO problem using proportional fairness.For this purpose, we introduce the concept of rho-NF (Nash Fairness) solution for BOCO achieving some Nash equilibrium based on proportional fairness. The factor rho > 0 is presented to reflect the relative importance between the two objectives. We first present the rho-NF solution concept and its characterization. We then show the Pareto efficiency of rho-NF solutions. In fact, each rho-NF solution is necessarily a Pareto-optimal solution but the inverse is not always true. Finally, we show that rho-NF solutions can be found by optimizing a linear combination of two objectives. This is a crucial aspect in developing efficient algorithms for identifying rho-NF solutions.Subsequently, we present the exact algorithms to determine the rho-NF solutions for BOCO. In some cases where the existence of rho-NF solution is not guaranteed, we design a binary search algorithm on the space of the ratio between two objectives which converges in a logarithmic (of fixed parameters depending on the data) number of iterations. It can determine the existence of the rho-NF solution and compute one in the affirmative case. In contrast, when there always exists and may be numerous rho-NF solutions, we develop a Newton-like recursive algorithm to identify all the rho-NF solutions. At each recursive call, we find a rho-NF solution by minimizing iteratively linear combinations of two objectives. Notice that the total number of recursive calls is bounded by the number of Pareto-optimal solutions. Furthermore, there exists one case where finding rho-NF solutions is equivalent to solving classical fractional programming. In this setting, we use the Newton-Dinkelbach method which is broadly applied to fractional programming. If two objectives are linear, the method finds rho-NF solutions in a strongly polynomial number of iterations, regardless of the structure of the feasible set.Finally, we evaluate our algorithms through various instances of BOCO. Computational experiments show the effectiveness of our algorithms, indicating their rapid convergence and efficiency in identifying rho-NF solutions. Furthermore, for some small instances, we compute the whole Pareto set to show that the rho-NF solution set is a strict subset of the Pareto set
Jooste, Chrisna. "Guidelines for the usability evaluation of a BI application within a coal mining organization". Diss., 2012. http://hdl.handle.net/10500/13329.
Texto completoInformation Science
M.Sc. (Information Systems)
Capítulos de libros sobre el tema "Bi-Criteria decision making"
Labreuche, Christophe. "Construction of a Bi-capacity and Its Utility Functions without any Commensurability Assumption in Multi-criteria Decision Making". En Information Processing and Management of Uncertainty in Knowledge-Based Systems, 294–303. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08795-5_31.
Texto completoVasalakis, Stamatios y Athanasios Spyridakos. "Resource Management: A Bi-Objective Methodological Approach for Routing in Crisis Situations". En Multiple Criteria Decision Making, 33–58. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-34892-1_3.
Texto completoZeferino, Emanuel Fernando, Khumbulani Mpofu, Olasumbo Makinde y Boitumelo Ramatsetse. "Establishment of an Appropriate Data Analytic Platform for Developing a Wisdom Manufacturing System Using Decision Techniques". En Lecture Notes in Mechanical Engineering, 622–29. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-28839-5_70.
Texto completoIjuin, Hiromasa, Takaki Nagao, Masakuni Tsunezawa, Kohei Sugiyama, Kazuyuki Tasaka y Tetsuo Yamada. "Designing a Reverse Supply Chain Network for Smartphones with Material-Based GHG Emissions and Costs Using Linear Physical Programming". En Lecture Notes in Mechanical Engineering, 127–35. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-28839-5_15.
Texto completoBallestero, Enrique y Carlos Romero. "A First Linkage: CP and Bi-Attribute Utility". En Multiple Criteria Decision Making and its Applications to Economic Problems, 77–101. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-2827-9_6.
Texto completoAruldoss, Martin, Miranda Lakshmi Travis y Prasanna Venkatesan Venkatasamy. "Identification of User Preference for Multi-Criteria Reporting in Business Intelligence". En Improving E-Commerce Web Applications Through Business Intelligence Techniques, 16–47. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3646-8.ch002.
Texto completoGarg, Harish. "Bi-Criteria Optimization for Finding the Optimal Replacement Interval for Maintaining the Performance of the Process Industries". En Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics, 643–75. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9644-0.ch025.
Texto completoAstor, Ron y Rami Benbenishty. "Surveys". En Mapping and Monitoring Bullying and Violence. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190847067.003.0012.
Texto completoActas de conferencias sobre el tema "Bi-Criteria decision making"
Shao, Lizhen, Depeng Zhao, Yinghai Shao, Jiwei Liu y Li Liu. "Bi-objective support vector machine and its application in microarray classification". En 2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM). IEEE, 2014. http://dx.doi.org/10.1109/mcdm.2014.7007203.
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