Journal of Intelligent & Fuzzy Systems - Volume 27, issue 6

Authors: Subulan, Kemal | Baykasoğlu, Adil | Saltabaş, Alper

Article Type: Research Article

Abstract: Recently, Reverse Logistics (RL) and product recovery options such as recycling, remanufacturing and reusing have become important issues due to the environmental, economical issues and legal regulations. Due to this fact, companies should take into account the utilized recovery option while preparing their strategic planning activities (like network design) instead of using traditional production planning models. However, since RL network design problems are in the class of NP-hard, solving large scaled problems by exact algorithms is very difficult. Therefore, many meta-heuristics optimization algorithms have been proposed to provide near optimal solutions for supply chain, RL and closed-loop supply chain network …design problems in the literature. In this paper, available decoding algorithms for solving generic RL design problems are revised so as to balance the problem without introducing any dummy node on the chromosome. Moreover, the proposed decoding procedure takes into account “equal transportation cost” situation. Then, a priority-based seeker optimization algorithm (SOA) which utilizes fuzzy reasoning procedure is developed for solution of the problem. In order to test performance of the algorithm, a numerical examined is provided and obtained results are compared with particle swarm optimization (PSO) algorithm which is another swarm intelligence technique. Computational results show that SOA is superior to PSO in terms of both solution quality and computational time for the example RL network design problem. Show more

Keywords: Reverse logistics network design, seeker optimization algorithm, particle swarm optimization, fuzzy reasoning

DOI: 10.3233/IFS-141335

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 6, pp. 2703-2714, 2014

Authors: Ai, Feng-Yi | Yang, Jing-Yi

Article Type: Research Article

Abstract: In this paper, we investigate the dynamic linguistic multiple attribute decision making problems with 2-tuple linguistic information. In order to aggregate dynamic 2-tuple linguistic information, some new dynamic aggregation operators are proposed: the dynamic 2-tuple weighted averaging (DTWA) operator, dynamic 2-tuple weighted geometric (DTWG) operator and dynamic 2-tuple weighted harmonic averaging (DTWHA) operator. Furthermore, some procedures based on the DTWA/DTWG/ DTWHA operators and TWA/TWG/ TWHA operators are developed to solve the dynamic 2-tuple linguistic multiple attribute decision making problems where all the decision information about attribute values takes the form of 2-tuple linguistic information collected at different periods. Finally, an …illustrative example for evaluating enterprise financial performance is given to verify the developed approach and to demonstrate its practicality and effectiveness. Show more

Keywords: Dynamic multiple attribute decision making, 2-tuple linguistic information, dynamic 2-tuple weighted averaging (DTWA) operator, dynamic 2-tuple weighted geometric (DTWG) operator, dynamic 2-tuple weighted harmonic averaging (DTWHA) operator, Enterprise financial performance

DOI: 10.3233/IFS-131094

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 6, pp. 2715-2723, 2014

Authors: Izadikhah, Mohammad | Saeidifar, Abolfazl | Roostaee, Razieh

Article Type: Research Article

Abstract: TOPSIS is one of most popular methods in the process of selecting a possible course of action from all of the alternatives. In this paper by using the nearest weighted interval approximation of the fuzzy numbers we try to extend TOPSIS in fuzzy environment. This paper proposes four new fuzzy TOPSIS methods. Two numerical examples are given to clarify the main results developed in this paper. In these examples we have applied some non-triangular and non-trapezoidal fuzzy numbers too. These methods are evaluated and compared with some other existing methods. We can say that, this is the main advantages of …the proposed methods, because, other fuzzy TOPSIS methods can't solve these kinds of problems. Show more

Keywords: TOPSIS, fuzzy numbers, nearest weighted interval approximation, interval data

DOI: 10.3233/IFS-131109

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 6, pp. 2725-2736, 2014

Authors: Zhang, Zhiming | Wu, Chong

Article Type: Research Article

Abstract: As a generalization of hesitant fuzzy set (HFS), interval-valued hesitant fuzzy set (IVHFS) permits an element's membership degree to be a set of several possible interval values and can therefore be used as an efficient mathematical tool for modeling people's hesitancy and uncertainty in multi-criteria decision making (MCDM). The Archimedean t-conorm and t-norm provide a generalization of a variety of other t-conorms and t-norms that include the Algebraic, Einstein, Hamacher and Frank t-conorms and t-norms as special cases. In this paper, we first present some new operational laws for interval-valued hesitant fuzzy elements (IVHFEs) based on the Archimedean t-conorm and …t-norm. Then, based on these operational laws, we develop several Archimedean t-conorm- and t-norm-based interval-valued hesitant fuzzy aggregation operators, which provide a family of interval-valued hesitant fuzzy aggregation operators that include the existing interval-valued hesitant fuzzy aggregation operators based on the Algebraic and Einstein t-conorms and t-norms as special cases. Some desired properties and special cases of the developed operators are investigated in detail. Furthermore, we develop an approach to MCDM under interval-valued hesitant fuzzy environments. Finally, an illustrative example is provided to show the effectiveness and practicality of the proposed operators and approach. Show more

Keywords: Multi-criteria decision making (MCDM), hesitant fuzzy set (HFS), interval-valued hesitant fuzzy set (IVHFS), Archimedean t-conorm and t-norm, interval-valued hesitant fuzzy aggregation operator

DOI: 10.3233/IFS-141143

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 6, pp. 2737-2748, 2014

Authors: Ai, Feng-Yi | Yang, Jing-Yi | Zhang, Ping-Dan

Article Type: Research Article

Abstract: In this paper, we investigate the multiple attribute decision making with hesitant fuzzy information. Motivated by the ideal of dependent aggregation, in this paper, we develop some dependent hesitant fuzzy aggregation operators: the dependent hesitant fuzzy ordered weighted averaging (DHFOWA) operator and the dependent hesitant fuzzy ordered weighted geometric (DHFOWG) operator, in which the associated weights only depend on the aggregated hesitant fuzzy arguments and can relieve the influence of unfair hesitant fuzzy arguments on the aggregated results by assigning low weights to those “false” and “biased” ones and then apply them to develop some approaches for multiple attribute group …decision making with hesitant fuzzy information. Finally, an illustrative example for supplier selection is given to verify the developed approach and to demonstrate its practicality and effectiveness. Show more

Keywords: Multiple attribute decision making, hesitant fuzzy information, dependent hesitant fuzzy ordered weighted averaging (DHFOWA) operator, dependent hesitant fuzzy ordered weighted geometric (DHFOWG) operator, supplier selection

DOI: 10.3233/IFS-141158

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 6, pp. 2749-2755, 2014

Authors: Megherbi, Hassina | Megherbi, Ahmed Chauki | Megherbi, Najla | Benmahammed, Khier

Article Type: Research Article

Abstract: This paper presents an evolution search methodology to automatically design a sectorial fuzzy controller (SFC). The evolution search methodology is an integer-coded evolutionary algorithm (EA) which involves two stages. At first stage, the proposed EA optimises the SFC for disturbance-free model of the plant to be controlled. The principal aim of the second stage is the robustness enhancement of the evolved SFC resulting from the former stage. Specifically, the proposed EA looks in the vicinity of the best SFC found in the first stage for a SFC that provide the best compromise between the control performance for a disturbance-free model …and for disturbed model. The sectorial properties were accommodated in the evolutionary search through a special parameterization of the fuzzy rule base (FRB) and the membership functions (MFs) of the SFC, repairing operator and special initialization of FRB chromosome part. Simulations were performed for direct-drive DC motor. The evolved SFC with the proposed design methodology found to provide very satisfactory performance under different types of disturbances. The trade-off between the accuracy performance and the robustness performance is also analysed during the evolution process. Show more

Keywords: Evolutionary algorithm, genetic fuzzy system, fuzzy logic control, sectorial fuzzy controller, automatic design of fuzzy controllers, robustness enhancement

DOI: 10.3233/IFS-141160

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 6, pp. 2757-2773, 2014

Authors: Liu, Ying | Li, Xiaozhong | Du, Ziping

Article Type: Research Article

Abstract: The repairable parallel system is an essential part of the maintenance support for high technology systems. The uncertain lifetimes and repair times of repairable parallel systems are usually treated as the stochastic variables, which have crisp parameters. However, in practice, the parameters may not be precisely represented due to lack of sufficient data. So in this paper, the lifetime and repair time of each component are assumed to have random fuzzy exponential distributions. Then a mathematical model of random fuzzy repairable parallel system composed by two non-identical components and one repair facility is established. Furthermore, the expressions of limiting availability …and steady state failure frequency of the random fuzzy repairable parallel system are proposed, respectively. Finally, a numerical example is presented. Show more

Keywords: Limiting availability, steady state failure frequency, parallel system, repairable system, random fuzzy variable

DOI: 10.3233/IFS-141212

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 6, pp. 2775-2784, 2014

Authors: Wang, Youwei | Liu, Yuanning | Zhu, Xiaodong

Article Type: Research Article

Abstract: Feature selection, which can reduce the dimensionality of vector space without sacrificing the performance of the classifier, is commonly used in spam filtering. As many classifiers cannot deal with the features with large dimensions, the noisy, irrelevant and redundant data should be removed from the feature spaces. In this paper, a two-step based hybrid feature selection method, called TFSM, is proposed. Firstly, we select the most discriminative features by an existing document frequency based feature selection method (called ODFFS). Secondly, we select the remaining features by combining the ODFFS and a newly proposed term frequency based feature selection method (called …NTFFS). Moreover, we propose a new optimizing meta-heuristic method, called GOPSO, to improve the convergence rate of standard particle swarm optimization. In the experiments, Support Vector Machine (SVM) and Naïve Bayesian (NB) classifiers are used on four corpuses: PU2, PU3, Enron-spam and Trec2007. The experimental results show that, TFSM is significantly superior to information gain, comprehensively measure feature selection, t-test based feature selection, term frequency based information gain and improved term frequency inverse document frequency method on four corpuses when SVM and NB are applied respectively. Show more

Keywords: Feature selection, spam filtering, particle swarm optimization, convergence rate, Support Vector Machine, Naïve Bayesian

DOI: 10.3233/IFS-141240

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 6, pp. 2785-2796, 2014

Authors: Farhadinia, B.

Article Type: Research Article

Abstract: There exist several types of measured functions that have been widely used for handling fuzzy multicriteria decision-making problems with vague (interchangeably, intuitionistic fuzzy) information. The main goal of this paper is to present firstly a comparative study of some existing measured functions underling their counter-intuitive examples and then a family of novel measured functions under vague environment is introduced.

Keywords: Vague set, intuitionistic fuzzy set, measured function, multi-attribute decision making

DOI: 10.3233/IFS-141241

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 6, pp. 2797-2808, 2014

Authors: Yordanova, Snejana

Article Type: Research Article

Abstract: Despite the new sophisticated controllers the linear PI/PID controllers keep the leading position in industrial implementations due to their simplicity, easy and well developed design and tuning, good system performance and robustness and universal application area. Various enhancements have been suggested to enlarge their range of operation with good performance. Fuzzy logic (FL) and genetic algorithms (GAs) offer proper intelligent solutions for improving the PI/PID controllers auto- tuning and adaptation to successfully deal with plant nonlinearity, inertia and changing parameters without plant model. The aim of this research is to develop a simple for engineering use method for design of …a fuzzy two-level controller (FTLC) of a linear PI/PID controller and a FL supervisor. The FL supervisor tunes on-line the scaling of the basic PI/PID controller's gains depending on performance indicators. The basic FTLC parameters are off-line optimized using GAs and a proposed fitness function of system performance and energy efficiency which is estimated in system simulation with a GA developed T-S plant model. The method is tested in real time control of the temperature in a laboratory – scale dryer. The result is decreased settling time, overshoot and energy consumption in the whole range of operation of the nonlinear plant. Show more

Keywords: Fuzzy logic supervisor, genetic algorithms, MATLAB™ real time temperature control, PI/PID controllers on-line auto-tuning, T-S plant modeling

DOI: 10.3233/IFS-141242

Citation: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 6, pp. 2809-2820, 2014