Relevant bibliographies by topics / Intuitionistic fuzzy programming

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Intuitionistic fuzzy programming'

Author: Grafiati
Published: 5 June 2025
Last updated: 15 July 2025

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Journal articles on the topic "Intuitionistic fuzzy programming"

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Ghosh, Payel, and Tapan Kumar Roy. "Role of Distance Metric in Goal Geometric Programming Problem (G^2 P^2) Under Imprecise Environment." International Journal of Fuzzy System Applications 8, no. 1 (2019): 65–82. http://dx.doi.org/10.4018/ijfsa.2019010104.

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The objective of this article is to tie a knot between distance measure and fuzzy and intuitionistic fuzzy optimization through goal programming. Firstly, a distance measure for an intuitionistic fuzzy number is developed, and then it is implemented into an intuitionistic fuzzy nonlinear goal programming. Then using some conditions, the distance measure of intuitionistic fuzzy number is converted into distance measure of fuzzy number and a comparative study using a numerical example is shown for highest applicability of distance measure based intuitionistic fuzzy goal programming than distance measure based fuzzy goal programming.
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Alrefaei, Mahmoud H., and Marwa Z. Tuffaha. "Fuzzy linear programming with the intuitionistic polygonal fuzzy numbers." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 2 (2024): 2242–53. https://doi.org/10.11591/ijece.v14i2.pp2242-2253.

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In real world applications, data are subject to ambiguity due to several factors; fuzzy sets and fuzzy numbers propose a great tool to model such ambiguity. In case of hesitation, the complement of a membership value in fuzzy numbers can be different from the non-membership value, in which case we can model using intuitionistic fuzzy numbers as they provide flexibility by defining both a membership and a non-membership functions. In this article, we consider the intuitionistic fuzzy linear programming problem with intuitionistic polygonal fuzzy numbers, which is a generalization of the previous polygonal fuzzy numbers found in the literature. We present a modification of the simplex method that can be used to solve any general intuitionistic fuzzy linear programming problem after approximating the problem by an intuitionistic polygonal fuzzy number with n edges. This method is given in a simple tableau formulation, and then applied on numerical examples for clarity.
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Alrefaei, Mahmoud H., and Marwa Z. Tuffaha. "Fuzzy linear programming with the intuitionistic polygonal fuzzy numbers." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 2 (2024): 2242. http://dx.doi.org/10.11591/ijece.v14i2.pp2242-2253.

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In real world applications, data are subject to ambiguity due to several factors; fuzzy sets and fuzzy numbers propose a great tool to model such ambiguity. In case of hesitation, the complement of a membership value in fuzzy numbers can be different from the non-membership value, in which case we can model using intuitionistic fuzzy numbers as they provide flexibility by defining both a membership and a non-membership functions. In this article, we consider the intuitionistic fuzzy linear programming problem with intuitionistic polygonal fuzzy numbers, which is a generalization of the previous polygonal fuzzy numbers found in the literature. We present a modification of the simplex method that can be used to solve any general intuitionistic fuzzy linear programming problem after approximating the problem by an intuitionistic polygonal fuzzy number with n edges. This method is given in a simple tableau formulation, and then applied on numerical examples for clarity.
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Xu, Yejun, and Huimin Wang. "IFWA and IFWGM Methods for MADM under Atanassov's Intuitionistic Fuzzy Environment." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 23, no. 02 (2015): 263–84. http://dx.doi.org/10.1142/s0218488515500117.

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In this paper, we first give the formula of possibility degree to rank the Atanassov's intuitionistic fuzzy numbers. Two methods called Atanassov's intuitionistic fuzzy weighted average (IFWA) and Atanassov's intuitionistic fuzzy weighted geometric mean (IFWGM) are developed to solve the multiple attribute decision making problems under Atanassov's intuitionistic fuzzy environment, in which the performance ratings of alternatives and relative importance of attributes are expressed with Atanassov's intuitionistic fuzzy sets. The IFWA and IFWGM methods, respectively, are treated as an auxiliary pair of fractional programming models and two linear programming (LP) solution procedures are proposed simultaneously by using Charnes and Cooper transformation. Furthermore, two algorithms which are based on the IFWA and IFWGM models, respectively, are developed to solve Atanassov's intuitionistic fuzzy decision making problems where attribute values and weights of attributes are all in Atanassov's intuitionistic fuzzy numbers. The order relationship between IFWA and IFWGM are investigated. Finally, a numerical example is illustrated to show the feasibility and effectiveness of the proposed methods.
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Bharati, S. K., and S. R. Singh. "Interval-Valued Intuitionistic Fuzzy Linear Programming Problem." New Mathematics and Natural Computation 16, no. 01 (2020): 53–71. http://dx.doi.org/10.1142/s1793005720500040.

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In many existing methods of linear programming problem (LPP), precise values of parameters have been used but parameters of LPP are imprecise and ambiguous due to incomplete information. Several approaches and theories have been developed for dealing LPP based on fuzzy set (FS), intuitionistic fuzzy set (IFS) which are characterized by membership degree, membership and non-membership degrees, respectively. It’s interesting to note that single membership and non-membership degrees do not deal properly the state of uncertainty and hesitation. Further, we face a kind of uncertainty occurs a kind of uncertainty. Interval-valued intuitionistic fuzzy sets (IV-IFS) is a perfect key for handling uncertainty and hesitation than FS and IFS. In this paper, we define an interval-valued intuitionistic fuzzy number (IV-IFN) and its expected interval and expected values. We also introduce the concept of interval-valued intuitionistic fuzzy linear programming problem (IV-IFLPP). Further, we find the solutions of IV-IFLPP and compare the obtained optimal solutions with existing methods [D. Dubey and A. Mehra, Linear programming with Triangular Intuitionistic Fuzzy Numbers, in Proc. of the 7th Conf. and of the European Society for Fuzzy Logic and Technology (EUSFLAT-LFA 2011), R. Parvathi and C. Malathi, Intuitionistic fuzzy linear optimization, Notes on Intuitionistic Fuzzy Sets 18 (2012) 48–56]. Proposed technique may be used successfully in various areas in the formulation of our country’s five year plans, these include transportation, food-grain storage, urban development, national, state and district level plans, etc., The Indian Railways may use IV-IFLPP technique for linking different railway zones in more realistic way. Agricultural research institutes may use proposed technique for crop rotation mix of cash crops, food crops and fertilizer mix. Airlines can apply IV-IFLPP in the selection of routes and allocation of aircrafts to different routes. Private and public sector oil refineries may use IV-IFLPP for blending of oil ingredients to produce finished petroleum products.
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R. Irene Hepzibah and R.Vidhya. "Modified new operations for triangular intuitionistic fuzzy numbers." Malaya Journal of Matematik 2, no. 03 (2014): 301–7. http://dx.doi.org/10.26637/mjm203/017.

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Intuitionistic fuzzy sets (IFS) are a generalization of the concept of fuzzy set. In standard intuitionistic fuzzy arithmetic operations, we have some grievances in subtraction and division operations. In this paper, modified new operations for subtraction and division on triangular intuitionistic fuzzy numbers (TIFNS) are defined. Finally an illustrative example for solving Intuitionistic fuzzy multi-objective linear programming problem (IFMOLPP) using these modified operators is provided.
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Pérez-Cañedo, Boris, José Luis Verdegay та Eduardo René Concepción-Morales. "An ε-Constraint Method for Multiobjective Linear Programming in Intuitionistic Fuzzy Environment". International Journal of Intelligent Systems 2023 (12 квітня 2023): 1–14. http://dx.doi.org/10.1155/2023/9677396.

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Effective decision-making requires well-founded optimization models and algorithms tolerant of real-world uncertainties. In the mid-1980s, intuitionistic fuzzy set theory emerged as another mathematical framework to deal with the uncertainty of subjective judgments and allowed to represent hesitancy in a decision-making problem. Nowadays, intuitionistic fuzzy multiobjective linear programming (IFMOLP) problems are a topic of extensive research, for which a considerable number of solution approaches are being developed. Among the available solution approaches, ranking function-based approaches stand out for their simplicity to transform these problems into conventional ones. However, these approaches do not always guarantee Pareto optimal solutions. In this study, the concepts of dominance and Pareto optimality are extended to the intuitionistic fuzzy case by using lexicographic criteria for ranking triangular intuitionistic fuzzy numbers (TIFNs). Furthermore, an intuitionistic fuzzy ε-constraint method is proposed to solve IFMOLP problems with TIFNs. The proposed method is illustrated by solving two intuitionistic fuzzy transportation problems addressed in two studies (S. Mahajan and S. K. Gupta’s, “On fully intuitionistic fuzzy multiobjective transportation problems using different membership functions,” Ann Oper Res, vol. 296, no. 1, pp. 211–241, 2021, and Ghosh et al.’s, “Multiobjective fully intuitionistic fuzzy fixed-charge solid transportation problem,” Complex Intell Syst, vol. 7, no. 2, pp. 1009–1023, 2021). Results show that, in contrast with Mahajan and Gupta’s and Ghosh et al.’s methods, the proposed method guarantees Pareto optimality and also allows to obtain multiple solutions to the problems.
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Oh, Hyonil, and Jungchol Cho. "A Fractional Programming Model for Improving Multiplicative Consistency of Intuitionistic Fuzzy Preference Relations." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 30, no. 05 (2022): 879–96. http://dx.doi.org/10.1142/s021848852250026x.

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In this paper, we propose a method that improves multiplicative consistency based on a fractional programming model to derive the normalized intuitionistic fuzzy priority weight vector from an intuitionistic fuzzy preference relation. To do so, a new definition is formulated that captures previous definitions for multiplicative consistency of intuitionistic fuzzy preference relations. A transformation formula is proposed to convert the normalized intuitionistic fuzzy priority weight vector into a multiplicative consistent intuitionistic fuzzy preference relation. By using the properties of some function, we construct a deviation matrix and prove that the elements in the intuitionistic fuzzy preference relation corresponding to the largest value in the deviation matrix is the most inconsistent. This method not only preserves a lot of the original preference judgments, but also reduce many operations in comparison with previous methods to improve multiplicative inconsistency. Several numerical examples are given to convince the proposed model and method.
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Thakur, P., and S. K. Sharma. "FUZZY MATRIX GAMES WITH INTUITIONISTIC FUZZY GOALS AND INTUITIONISTIC FUZZY LINEAR PROGRAMMING DUALITY." Advances in Mathematics: Scientific Journal 9, no. 8 (2020): 5421–31. http://dx.doi.org/10.37418/amsj.9.8.13.

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Thakur, P., and S. K. Sharma. "FUZZY MATRIX GAMES WITH INTUITIONISTIC FUZZY GOALS AND INTUITIONISTIC FUZZY LINEAR PROGRAMMING DUALITY." Advances in Mathematics: Scientific Journal 9, no. 8 (2020): 5561–71. http://dx.doi.org/10.37418/amsj.9.8.25.

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Dissertations / Theses on the topic "Intuitionistic fuzzy programming"

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Yu-TaTsai and 蔡侑達. "Formulating Intuitionistic Fuzzy Regression Models By Mathematical Programming Methods." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/7n3jf7.

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碩士<br>國立成功大學<br>工業與資訊管理學系<br>105<br>Regression analysis is one of the most widely used decision making tools. It allows decision makers to determine the relationship between input variables and output variables. In a statistical regression analysis, data is always precise figures, which are called crisp values. However, in the complex real-world environment, data may be uncertain, written in linguistic terms, or based on personal subjective attitudes. Therefore, fuzzy set theory was developed to deal with these data. In order to express the essence of uncertainty better, scholars proposed the concept of intuitionistic fuzzy sets (IFS) as a generalization of the fuzzy set theory. In addition to including positive information, it also includes negative information. There have been few studies of intuitionistic fuzzy regression (IFR) models. The direction of these studies was decided by three elements: data-type and parameter-type, solution approaches, and computation of the estimation error. In this study, the available data for both input variables and output variables are assumed to be intuitionistic fuzzy numbers (IFN), and the model parameters are crisp numbers. The parameters are crisp values rather than IFN because IFN multiplied with each other will bring about an over-increase in the spread of the IFN. In other words, the fuzziness of numbers will be over-increased. Different from the traditional solution methods such as the least-squares method, this study uses mathematical programming methods. The concept of decomposition rules and IFN-cuts are also used to build models. Two different approaches are proposed in this study. The predictive ability of the obtained models is evaluated by using similarity and distance measures. The results indicate that the models proposed in this study are better than their counterparts.
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Han, Wen-Hsin, and 韓文欣. "Fuzzy Multiattribute Decision Making Based on Interval-Valued Intuitionistic Fuzzy Values, Interval-Valued Intuitionistic Fuzzy Weighted Averaging Operator, and Nonlinear Programming Methodology." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/y8vcyj.

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碩士<br>國立臺灣科技大學<br>資訊工程系<br>106<br>In this thesis, we propose a new fuzzy multiattribute decision making method based on interval-valued intuitionistic fuzzy values, the interval-valued intuitionistic fuzzy weighted averaging operator, and the nonlinear programming methodology. Firstly, the proposed method calculates the largest ranges of interval-valued intuitionistic fuzzy weights of attributes and modifies unreasonable ranges of interval-valued intuitionistic fuzzy weights. Then, it gets the transformed decision matrix based on the score function of interval-valued intuitionistic fuzzy values and the decision matrix provided by the decision maker. Then, it constructs the nonlinear programming model based on the obtained transformed decision matrix and the obtained largest ranges of interval-valued intuitionistic fuzzy weights of attributes. Then, it gets the optimal weights of the attributes based on the obtained nonlinear programming model. Then, it calculates the weighted evaluating interval-valued intuitionistic fuzzy values of the alternatives based on the decision matrix, the obtained optimal weights of the attributes and the interval-valued intuitionistic fuzzy weighted averaging operator. Finally, it gets the preference order of the alternatives based on the score function, the accuracy function, the membership uncertainty index and the hesitation uncertainty index of interval-valued intuitionistic fuzzy values. The proposed fuzzy multiattribute decision making method can overcome the drawback of the existing methods. It provides us with a very useful way for fuzzy multiattribute decision making in interval-valued intuitionistic fuzzy environments.
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Cheng, Mei-Fang, and 鄭美芳. "Linear Programming Model of an Inconsistent Multiplicative Intuitionistic Fuzzy Preference Relation." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/q66fr4.

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碩士<br>國立高雄應用科技大學<br>工業工程與管理系碩士在職專班<br>106<br>This paper considers the problem of the goal programming optimization model proposed by Gong et al.(2009) for an inconsistent multiplicative intuitionistic fuzzy preference relation. For the three alternatives, a reduced goal programming optimization model is proposed in this paper. Three special inconsistent multiplicative intuitionistic fuzzy preference relations are considered which make the optimal upper priority weights equal to the lower priority weights. For each special inconsistent multiplicative intuitionistic fuzzy preference relation, four cases are analyzed. We obtain the explicit priority weights and objective values. So we can efficiently obtain these optimal solutions without using goal programming optimization model. These results provide insights into the Gong et al. inconsistent multiplicative intuitionistic fuzzy preference relation for the fuzzy decision problems.
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Hsu, Ya-Ju, and 許雅茹. "Applying Intuitionistic Fuzzy Multi-objective Programming to Waste PC Recycling Fees Formulation." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/69033019539346599112.

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碩士<br>淡江大學<br>管理科學學系碩士班<br>101<br>As new information products are constantly innovated, a large number of electronic wastes are to be processed which cause the importance of recycling. Republic of China established Recycling Fund Management Board to promote the recycling business, and it depends on polluter-pays principle to levy the recycling and treatment fee subsidizing the recycling treatment plants for waste reduction. This study applies intuitionistic fuzzy multi-objective to Taiwan’s waste PC recycling and treatment fee formulation. In terms of Recycling Fund Management Board, we set up the following goals: Maximize the recycling ratio and Minimize the recycling and treatment fee to expect best benefits. This study introduces the fuzzy regression to recycling ratio for error reduction. In intuitionistic fuzzy multi-objective model, the concept of non-membership function adding the accuracy is a new idea apart from the concept of membership. This study finds three results as follows: First, the recycling subsidy fee is a key factor to raise recycling ratio and the current recycling and treatment fee is appropriate. Second, there is a positive correlation between the recycling subsidy fee and the recycling ratio. Finally, the mutual fund ratio is higher than the current and the nonoperation fund is lower than the current to confirm the operation efficiency.
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Wei-MingHou and 侯瑋明. "Developing Intuitionistic Fuzzy Goal Programming Approaches to Solve Multi-level Decision-making Problems." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/tz5f74.

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Huang, Zhi-Cheng, and 黃智呈. "Multiattribute Decision Making Based on Interval-Valued Intuitionistic Fuzzy Values and the Linear Programming Methodology." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/52333321606816666877.

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碩士<br>國立臺灣科技大學<br>資訊工程系<br>104<br>In recent years, some methods have been presented based on interval-valued intuitionistic fuzzy sets for multiattribute decision making. In this thesis, we propose a new multiattribute decision making method based on interval-valued intuitionistic fuzzy values and the linear programming methodology. The weights of attributes and the evaluating values of alternatives are represented by interval-valued intuitionistic fuzzy values. The proposed method has the advantage that it is simpler than the existing methods for multiattribute decision making in interval-valued intuitionistic fuzzy environments. The proposed method provides us with a very useful way for multiattribute decision making in interval-valued intuitionistic fuzzy environments.
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Chen, Boris Bor-Yeu, and 陳柏宇. "A Study of Setting the Subsidy of Waste Printers Recycling in Taiwan - Approaches of KKT Conditions and Intuitionistic Fuzzy Sets for Bi-level Programming." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/26257816860632235787.

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碩士<br>淡江大學<br>管理科學研究所碩士班<br>99<br>This research applies bi-level programming to make a decision of the subsidy to recycling industries for waste printers in Taiwan. The upper-level decision unit is design for the social welfare system; the lower-level unit is modeled as the recycling industries. The different and conflict of these two objectives can be simulated by the bi-level programming model. This research solves the model through KKT conditions and 0-1 variable transformation, fuzzy approach and intuitionistic fuzzy approach, and compares the results of these approaches with current subsidy for obtaining a better managerial control. 　　Recycling Fund Management Board (RFMB), Environment Protection Administration of ROC Government was founded being responsible for resource recycling. The RFMB levy the fee from responsible manufactures or importers, and give the recycling and treatment fee to the recycling industries. The recycling industries also give the incentives to the populace who come to recycle their wastes. The upper-level, it aims to increase the recycling rate, reduce the recycling and treatment fees of waste printers, and reduce the administrative cost. The goal of the lower-level is to increase their profits. For comparing the managerial control, this research applies KKT conditions and 0-1 variable transformation which are upper-level model; the fuzzy approach and intuitionistic fuzzy approach which is lower-level model. 　　As a result, the profits of recycling industries arise when the resources value increase, and the profit are depending on the recycling rate. Besides, the correlation between the incentives and recycling rate are positive. Higher incentives get higher recycling rate, then the profit of recycling industries increased and the environment pollution can be reduced. Thus, this research can improve recycling rate and the circumstance of social welfare system. Lastly, 0-1 programming has larger value for the recycling and treatment fee, but the incentives are lower than fuzzy approach and intuitionistic fuzzy approach. It causes the lower recycling industries profit and recycling rate. The results can be an option for setting the subsidy on waste printers for RFMB.
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Book chapters on the topic "Intuitionistic fuzzy programming"

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Yang, Ji-hui, Xue-gang Zhou, and Pei-hua Wang. "Geometric Programming with Intuitionistic Fuzzy Coefficient." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66514-6_20.

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Kheiri, Zeinab, and Bing-yuan Cao. "Posynomial Geometric Programming with Intuitionistic Fuzzy Coefficients." In Fuzzy Systems & Operations Research and Management. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19105-8_2.

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Kumar, Sandeep. "The Relationship Between Intuitionistic Fuzzy Programming and Goal Programming." In Advances in Intelligent Systems and Computing. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-3322-3_20.

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Sidhu, Sukhpreet Kaur, and Amit Kumar. "Mehar Methods to Solve Intuitionistic Fuzzy Linear Programming Problems with Trapezoidal Intuitionistic Fuzzy Numbers." In Performance Prediction and Analytics of Fuzzy, Reliability and Queuing Models. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0857-4_20.

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Ozkan, Omer, and Serhat Aydin. "Supplier Selection with Intuitionistic Fuzzy AHP and Goal Programming." In Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23756-1_100.

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Li, Deng-Feng. "Matrix Games with Goals of Intuitionistic Fuzzy Sets and Linear Programming Method." In Decision and Game Theory in Management With Intuitionistic Fuzzy Sets. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40712-3_10.

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Bharati, S. K., A. K. Nishad, and S. R. Singh. "Solution of Multi-Objective Linear Programming Problems in Intuitionistic Fuzzy Environment." In Advances in Intelligent Systems and Computing. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1602-5_18.

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Malik, Manisha, and S. K. Gupta. "Development and Optimization of Quadratic Programming Problems with Intuitionistic Fuzzy Parameters." In Combinatorial Optimization Under Uncertainty. CRC Press, 2023. http://dx.doi.org/10.1201/9781003329039-11.

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Li, Deng-Feng. "Bi-matrix Games with Payoffs of Intuitionistic Fuzzy Sets and Bilinear Programming Method." In Decision and Game Theory in Management With Intuitionistic Fuzzy Sets. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40712-3_11.

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Li, Deng-Feng. "Matrix Games with Payoffs of Intuitionistic Fuzzy Sets and Linear and Nonlinear Programming Methods." In Decision and Game Theory in Management With Intuitionistic Fuzzy Sets. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40712-3_7.

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Conference papers on the topic "Intuitionistic fuzzy programming"

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Gulia, Pinki, Vikrant Sharma, Manik Rakhra, Kapil Jairath, Sakshi Suri, and Rakesh Kumar. "Transportation Planning Decision-Making Using Intuitionistic Fuzzy Programming." In 2024 7th International Conference on Contemporary Computing and Informatics (IC3I). IEEE, 2024. https://doi.org/10.1109/ic3i61595.2024.10828887.

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Chauhan, Abhishek, and Sumati Mahajan. "Generalized Intuitionistic Fuzzy Programming for Non-Linear Multiobjective Optimization using T-Norms and T-Conorms." In 2024 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2024. http://dx.doi.org/10.1109/fuzz-ieee60900.2024.10611962.

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Dubey, Dipti, and Aparna Mehra. "Linear programming with Triangular Intuitionistic Fuzzy Number." In 7th conference of the European Society for Fuzzy Logic and Technology. Atlantis Press, 2011. http://dx.doi.org/10.2991/eusflat.2011.78.

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Yi, Liu, Li Wei-min, and Xu Xiao-lai. "Intuitionistic Fuzzy Bilevel Programming by Particle Swarm Optimization." In 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application (PACIIA). IEEE, 2008. http://dx.doi.org/10.1109/paciia.2008.281.

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Parvathi, R., and C. Malathi. "Linear programming using symmetric triangular intuitionistic fuzzy numbers." In NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2012: International Conference of Numerical Analysis and Applied Mathematics. AIP, 2012. http://dx.doi.org/10.1063/1.4756601.

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Xu, Xiao-lai, and Ying-jie Lei. "Improved Intuitionistic Fuzzy Programming Based on Differential Evolution Algorithm." In 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application (PACIIA). IEEE, 2008. http://dx.doi.org/10.1109/paciia.2008.282.

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Chu, Junfeng, and Xinwang Liu. "A mathematical programming method for the multiple attribute decision making with interval intuitionistic fuzzy values." In 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2014. http://dx.doi.org/10.1109/fuzz-ieee.2014.6891706.

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Gong, Zai-Wu, Chong-Lan Guo, Tian-Xiang Yao, and Yuan-Yuan He. "The quadratic programming method for intuitionistic fuzzy group decision making." In 2011 International Conference on Grey Systems and Intelligent Services (GSIS 2011). IEEE, 2011. http://dx.doi.org/10.1109/gsis.2011.6044134.

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Tamani, Nouredine. "Intuitionistic fuzzy bipolar approach for flexible querying in e-commerce applications." In 2015 12th International Symposium on Programming and Systems (ISPS). IEEE, 2015. http://dx.doi.org/10.1109/isps.2015.7244972.

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Jayalakshmi, M., D. Anuradha, V. Sujatha, and G. Deepa. "A simple mathematical approach to solve intuitionistic fuzzy linear programming problems." In RECENT TRENDS IN PURE AND APPLIED MATHEMATICS. AIP Publishing, 2019. http://dx.doi.org/10.1063/1.5135200.

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