Journal of Intelligent & Fuzzy Systems - Volume 32, issue 1

Authors: Wang, Ke | Zhou, Jian | Ralescu, Dan A.

Article Type: Research Article

Abstract: This paper introduces arithmetic operations for LR mixed fuzzy random variables commonly used in practice for modeling fuzzy stochastic phenomena. The operations are proposed based on mean chance measure, which as a natural extension of both the probability of a random event and the credibility of a fuzzy event, measures the mean or expected (in the sense of probability) credibility that the fuzzy random event occurs. Following from the proposed operational laws, the mean chance distributions of LR mixed fuzzy random variables can be deduced explicitly rather than obtained by simulation, which will provide greater convenience for the decision making …or optimization in mixed fuzzy and random environments. Furthermore, some important conclusions on the expected value operator defined via the mean chance measure as well as applications of the proposed arithmetic operations in system reliability analysis are also presented. Show more

Keywords: Fuzzy random variable, mean chance, operational law, expected value, reliability analysis

DOI: 10.3233/JIFS-152173

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 451-466, 2017

Authors: Kazemi, Seyed Mahmood | Rabbani, Masoud | Tavakkoli-Moghaddam, Reza | Shahreza, Farid Abolhassani

Article Type: Research Article

Abstract: The problem of delivering blood products from community blood centers to the demand points including hospital blood banks falls within the context of perishable inventory-routing problems (PIRP). This is due to the fact that the delivery should be made on the right time with the right delivery quantity at the right place such that the total possible perished items as well as routing and inventory costs are minimized. However, some unique characteristics of blood logistics including assigned and unassigned inventories, crossmatch release period, transfusion to crossmatch ratio and older-first policy have made the problem more difficult than the routine PIRPs …and thus proposing a new modeling of the problem is required. In this paper, we first develop a mixed integer programming formulation for blood inventory-routing problem. Then, to cope with uncertainties, a novel robust possibilistic programming (RPP) approach is proposed. Afterward, a novel iterative branch-and-cut is developed to solve a number of numerical examples to optimality. Finally, by implementing a test scenario on the data inspired from a real Iranian blood supply chain, the significance and applicability of the proposed model and RPP approach is proven. Show more

Keywords: Healthcare management, blood inventory-routing, perishable products, robust possibilistic programming, branch-and-cut algorithm

DOI: 10.3233/JIFS-152175

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 467-481, 2017

Authors: Mandal, Prasenjit | Ranadive, A.S.

Article Type: Research Article

Abstract: This paper is devoted to propose generalized L-fuzzy variable precision rough sets, based on generalized residuated lattices with conjunctions not necessarily commutative over two universes, as a generalization of the notion of L-fuzzy variable precision rough sets based on residuated lattices with commutative conjunctions over one universe only. Then we define and investigate several classes of generalized L-fuzzy variable precision rough sets. The topological properties and granular representation of generalized L-fuzzy variable precision rough sets are also given. Our main concern is to propose a real number valued function for each approximation operator in generalized L-fuzzy variable precision rough sets …and to measure its approximating ability. We observe that the functions of lower and upper approximation operators are natural generalizations of belief and plausibility functions respectively as given in the evidence theory. Using these functions, accuracy measure and degree of roughness is defined for generalized L-fuzzy variable precision rough sets. As an application of generalized L-fuzzy variable precision rough sets, I-fuzzy variable precision rough sets are proposed on the unit interval I = [0, 1], based on generalized residuated lattices induced by left-continuous pseudo-t-norms. Show more

Keywords: Generalized residuated lattices, pair of weak negations, generalized L-fuzzy variable precision rough sets, belief function, pseudo-t-norms

DOI: 10.3233/JIFS-152255

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 483-497, 2017

Authors: Rashid, Maliha | Shahzad, Aqeel | Azam, Akbar

Article Type: Research Article

Abstract: In this paper, we prove some fixed point theorems for L -fuzzy mappings in left K-sequentially and rightK-sequentially complete quasi-pseudo metric spaces.These are the generalizations of many results in the recent literature. Some examples are also included to support our results.

Keywords: L-fuzzy mapping, fixed point, quasi-pseudo-metric, left K-sequentially complete, right K-sequentially complete

DOI: 10.3233/JIFS-152261

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 499-507, 2017

Authors: Liu, Hongbing | Li, Weihua | Li, Ran

Article Type: Research Article

Abstract: Granular computing (GrC) is a frame computing paradigm that realizes the transformation between two granule spaces with different granularities. A comparative analysis of granular computing clustering is discussed in the paper. Firstly, a granule is defined as the form of vectors by the center and the granularity, especially, an atomic granule is induced by a point which has the granularity 0. Secondly, the join operator realizes the transformation from the granule space with smaller granularity to the granule space with lager granularity, and is used to form the granular computing clustering (GrCC) algorithms. Thirdly, the granular computing clustering algorithms are …evaluated from the view of set, such as Global Consistency Error (GCE), Normalized Variation of Information (NVI), and Rand Index (RI). The superiority and feasibility of GrCC are compared with Kmeans and FCM by experiments on the benchmark data sets. Show more

Keywords: Granule space, granular computing, granular computing clustering

DOI: 10.3233/JIFS-152327

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 509-519, 2017

Authors: Singh, Vishnu Pratap | Chakraborty, Debjani

Article Type: Research Article

Abstract: This paper represents the bi-level linear programming problem in an imprecise and uncertain mixed environment. The aim of this paper is to introduce coefficients of leader and the follower’s objective function and the constraints as the fuzzy random variable. To determine the optimal value of the leader and follower’s objectives a new methodology is developed for bi-level linear programming model in the presence of fuzzy random variable. A numerical example is solved to demonstrate the methodology.

Keywords: Bi-level programming, fuzzy random variable, two stage stochastic programming, fuzzy goal programming

DOI: 10.3233/JIFS-152354

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 521-528, 2017

Authors: An, Truong Vinh | Van Hoa, Ngo | Tuan, Nguyen Anh

Article Type: Research Article

Abstract: In this paper, we study the global existence and uniqueness results for interval-valued functional integro-differential equations and impulsive hybrid interval-valued functional integro-differential equations under generalized Hukuhara derivative. Some examples are given to illustrate these results.

Keywords: Interval differential equation, interval integro-differential equation, impulsive hybrid interval integro-differential equations, interval functional integro-differential equation, generalized Hukuhara derivative

DOI: 10.3233/JIFS-152405

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 529-541, 2017

Authors: Zhou, Shenghan | Li, Lei | Yang, Min | Chang, Wenbing

Article Type: Research Article

Abstract: This paper focuses on the multiple attribute decision making problems in evaluation of experiment platforms with 2-tuple linguistic information. The traditional teaching can’t meet the demand of increasing talent training. The requirement of educational quality has been more and higher in the background of the information science development. The modern experiment teaching has some major problems: inadequate funding, carrying experiment teaching in remote and continuing education is difficulty, practice and innovation ability limited by resource. The research design the 2-tuple power Einstein weighted average (2TPEWA) operator for aggregating 2-tuple linguistic information inspired by the idea of power aggregation and Einstein …operations. Then the 2TPEWA operator is used to construct the model for multiple attribute decision making with 2-tuple linguistic information. In the end, an example for performance evaluation of experiment platforms is proposed to test the given method and to prove its practicality and effectiveness. Show more

Keywords: Multiple attribute decision making (MADM), 2-tuple linguistic variables, power average operator, 2-tuple power Einstein weighted average (2TPEWA) operator, performance evaluation, experiment platforms

DOI: 10.3233/JIFS-152434

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 543-549, 2017

Authors: Kardan, Iman | Akbarzadeh-T, Mohammad-R | Akbarzadeh, Alireza | Kalani, Hadi

Article Type: Research Article

Abstract: In this paper, the notion of generalized differentiability is extended to quasi type 2 fuzzy mappings and the concept of quasi type 2 fuzzy derivative is defined. Then, based on this definition and by using the alpha-cut extension principle, an effective method is proposed for solving quasi type 2 fuzzy differential equations. Finally, the applicability of the proposed method is demonstrated through several examples.

Keywords: Fuzzy derivative, generalized differentiability, fuzzy differential equations, quasi type 2 fuzzy sets

DOI: 10.3233/JIFS-152470

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 551-563, 2017

Authors: Roul, J.N. | Maity, K. | Kar, S. | Maiti, M.

Article Type: Research Article

Abstract: The aim of this paper is to formulate and solve an optimal control problem under finite time horizon in fuzzy environment using fuzzy variational principle. Here an imperfect/defective item is produced to meet a time-dependent demand for a finite time period having no stock at both ends. The unit production cost is a function of production rate and also dependent on raw material cost, development costs due to durability and wear-tear cost. The cost function which consists of revenue, production and holding costs is formulated as a Fixed-Final Time and Fixed State System optimal control problem with finite time horizon. …Here production rate is unknown and considered as a control variable and stock level is taken as a state variable. It is formulated to optimize the production rate so that total cost is minimum. For the fuzzy model, the production rate, stock level, inventory cost and development cost are taken as fuzzy. The models are solved by using conventional Variational Principle for crisp model and Fuzzy Variational Principle (FVP) for fuzzy model. For simulation, Mathematica-9.0 and the non-linear optimization technique Generalised Reduced Gradient Method (LINGO 11.0) have been used. The optimum results are illustrated both numerically and graphically. For the fuzzy model, the membership functions of fuzzy outputs are presented. The results of crisp model are also obtained from the fuzzy model. Show more

Keywords: Fuzzy variational principle, finite time horizon, imperfect production system, optimal control problem

DOI: 10.3233/JIFS-152503

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 565-577, 2017