ALBERT

Description: In this paper, we investigate the multiple attribute decision making (MADM) problem based on the arithmetic and geometric aggregation operators with hesitant fuzzy linguistic information. Then, motivated by the ideal of traditional arithmetic and geometric operation, we have developed some aggregation operators for aggregating hesitant fuzzy linguistic information: hesitant fuzzy linguistic arithmetic aggregation operators, hesitant fuzzy linguistic geometric aggregation operators, hesitant fuzzy linguistic correlated aggregation operators, induced hesitant fuzzy linguistic aggregation operators, induced hesitant fuzzy linguistic correlated aggregation operators, hesitant fuzzy linguistic prioritized aggregation operators, hesitant fuzzy linguistic power aggregation operators. Then, we have utilized these operators to develop some approaches to solve the hesitant fuzzy linguistic multiple attribute decision making problems. Finally, a practical example is given to verify the developed approach. Content Type Journal Article Pages - DOI 10.3233/IFS-130977 Authors Rui Lin, Institute of Decision Sciences, School of Economics and Management, Chongqing University of Arts and Sciences, Yongchuan, China Xiaofei Zhao, Institute of Decision Sciences, School of Economics and Management, Chongqing University of Arts and Sciences, Yongchuan, China Hongjun Wang, Institute of Decision Sciences, School of Economics and Management, Chongqing University of Arts and Sciences, Yongchuan, China Guiwu Wei, Institute of Decision Sciences, School of Economics and Management, Chongqing University of Arts and Sciences, Yongchuan, China Journal Journal of Intelligent and Fuzzy Systems Online ISSN 1875-8967 Print ISSN 1064-1246

Description: In a process using monitoring with p-control charts or np-control charts, due to the uncertainty of the attribute data, traditional control charts may be insufficient. In this case, fuzzy control charts are pertinent control techniques used to capture vagueness. Many studies in the literature are configured with transformation techniques at the decision stage, and in this study, fuzzy control charts are constructed using rules. Therefore, fully fuzzy control charts are first introduced for fuzzy [( p )\tilde]-control charts based on constant sample size and variable sample size, and fuzzy n [( p )\tilde]-control charts are subsequently introduced using decision rules for the process state conditions. Therefore, “rather in control” and “rather out of control” decisions can be considered in monitoring of the process. Content Type Journal Article Pages - DOI 10.3233/IFS-130986 Authors Nihal Erginel, Industrial Engineering Department, Anadolu University, Eskisehir, Turkey Journal Journal of Intelligent and Fuzzy Systems Online ISSN 1875-8967 Print ISSN 1064-1246

Description: As generalize of the hesitant fuzzy sets, hesitant interval-valued fuzzy sets (HIVFSs), which permits the memberships of an element to a given set having a few different interval values in [0,1] rather than real numbers, can be considered as a powerful tool to express uncertain information in the human decision making process. Based on the traditional Hamming distance, Euclidean distance, Hausdorff distance, and generalized distance, in this paper, we propose a variety of distance measures for hesitant interval-valued fuzzy sets, based on which the corresponding similarity measures can be obtained. We investigate the connections of the aforementioned distance measures and further develop a number of hesitant interval-valued ordered weighted distance measures and hesitant interval-valued ordered weighted similarity measures. They can alleviate the influence of unduly large (or small) deviations on the aggregation results by assigning them low (or high) weights. Finally, we shall present a numerical example to show potential evaluation of emerging technology commercialization with hesitant interval-valued fuzzy information in order to illustrate the method proposed in this paper. Content Type Journal Article Pages - DOI 10.3233/IFS-130975 Authors Guiwu Wei, Institute of Decision Sciences, School of Economics and Management, Chongqing University of Arts and Sciences, Yongchuan, China Rui Lin, Institute of Decision Sciences, School of Economics and Management, Chongqing University of Arts and Sciences, Yongchuan, China Hongjun Wang, Institute of Decision Sciences, School of Economics and Management, Chongqing University of Arts and Sciences, Yongchuan, China Journal Journal of Intelligent and Fuzzy Systems Online ISSN 1875-8967 Print ISSN 1064-1246

Description: Optimal capacitor placement problem is a significant and precious strategy which can be supposed as an always appropriate solution to reduce the operating costs in the power systems. Nevertheless, as the result of nonlinear and discrete characteristics of this problem, traditional optimization methods can not solve it effectively. Therefore, this paper proposes a novel optimization framework based on shuffled frog leaping algorithm (SFLA) to solve the optimal capacitor placement and sizing problem properly. In this regard, a new modification approach based on the mutation and crossover operators is suggested to improve the local search ability of this algorithm. The effectiveness and satisfying performance of the proposed method is assessed on two IEEE test systems. Comparative results sow the superiority of the proposed optimization method than the other popular methods in the area. Content Type Journal Article Pages - DOI 10.3233/IFS-130997 Authors Mohammad-Reza Akbari-Zadeh, Nourabad Mamasani Branch, Islamic Azad University, Nourabad Mamasani, Iran Mahdi Vosoogh, Nourabad Mamasani Branch, Islamic Azad University, Nourabad Mamasani, Iran Mohammad Mirjavadi, Nourabad Mamasani Branch, Islamic Azad University, Nourabad Mamasani, Iran Alireza Abbasi, Nourabad Mamasani Branch, Islamic Azad University, Nourabad Mamasani, Iran Journal Journal of Intelligent and Fuzzy Systems Online ISSN 1875-8967 Print ISSN 1064-1246

Description: This paper considers supply chain models with a manufacturer acting as the leader and two competitive retailers acting as followers under a fuzzy decision environment. The parameters of demand function and manufacturing cost are treated as the triangular fuzzy variables. Two retailers are assumed to pursue two kinds of competitive behavior: Cournot and Stackelberg. For each case, optimum policy of the expected value and two chance-constrained programming models are derived. Finally, a numerical example is provided to illustrate the results of proposed models. It is shown that in fuzzy models, the different competitive behaviors of two retailers do not affect the optimal pricing strategies of the manufacturer, and the confidence level of the profits for supply chain members affects the optimal sale price, wholesale price and profits. Content Type Journal Article Pages - DOI 10.3233/IFS-130994 Authors Shengju Sang, Department of Economics, Heze University, Heze, China Journal Journal of Intelligent and Fuzzy Systems Online ISSN 1875-8967 Print ISSN 1064-1246

Description: Today, preference relations are among the most common types of expressing decision maker's preference information found in uncertainty research. Intuitionistic multiplicative preference relation can reflect our intuition more objectively and it was proposed by Xia et al. [20] recently. In this article, we first develop some aggregation operators for intuitionistic multiplicative numbers, such as the intuitionistic multiplicative weighted averaging operator and intuitionistic multiplicative ordered weighted averaging operator. Their desirable properties are also investigated in detail. Furthermore, based on the proposed aggregation operators, we further introduce a group decision making method based on intuitionistic multiplicative preference relations. Finally, a real example about personnel selection is given to illustrate the effectiveness of our method, the numeric comparison between our group decision making method and the ones of Xia et al. [20] are also provided. Content Type Journal Article Pages - DOI 10.3233/IFS-130984 Authors Dejian Yu, School of Information, Zhejiang University of Finance and Economics, Hangzhou, China Lincong Fang, School of Information, Zhejiang University of Finance and Economics, Hangzhou, China Journal Journal of Intelligent and Fuzzy Systems Online ISSN 1875-8967 Print ISSN 1064-1246

Description: Artificial life uses biological knowledge and techniques to solve different engineering, management, control and computational problems. Natural systems teach us that very simple individual organisms can form systems capable of performing highly complex tasks by dynamically interacting with each other. In this study, artificial life based approaches are handled and incorporated to enable a real-time water level control. The process was first modelled using NARX type Artificial Neural Network. A fuzzy controller was then attached to the model. For a better performance, fuzzy controller membership function boundary values and action values were optimized simultaneously. The optimization process was performed using genetic algorithm and ant colony optimization algorithm, respectively. Finally, the performance of the controllers was discussed further by considering the system outputs. The developed structure replaces the tedious process of trial-and-error for better combination of fuzzy parameters and can settle the problem of designing fuzzy controller without an expert's experience. Content Type Journal Article Pages - DOI 10.3233/IFS-131003 Authors Turker Tekin Erguzel, Computer Engineering Department, Uskudar University, Uskudar, Istanbul, Turkey Erbil Akbay, Electronic–Computer Education Department, Marmara University, Technical Education Faculty, Kadikoy, Istanbul, Turkey Journal Journal of Intelligent and Fuzzy Systems Online ISSN 1875-8967 Print ISSN 1064-1246

Description: In this paper, we first introduce some operations on interval-valued intuitionistic fuzzy sets, such as Einstein sum, Einstein product, Einstein exponentiation, etc., and further develop the induced interval-valued intuitionistic fuzzy Einstein ordered weighted average (I-IVIFEOWA) operator. We also establish some desirable properties of this operator, such as commutativity, idempotency and monotonicity. Then, we apply the induced interval-valued intuitionistic fuzzy Einstein ordered weighted average(I-IVIFEOWA) operator based on the data mining to deal with multiple attribute decision making under interval-valued intuitionistic fuzzy environments. Finally, an illustrative example about selecting an ERP system is given to verify the developed approach and to demonstrate its practicality and effectiveness. Content Type Journal Article Pages - DOI 10.3233/IFS-131000 Authors Xuesen Cai, College of GeoExploration Science and Technology, Jilin University, Changchun, China Liguo Han, College of GeoExploration Science and Technology, Jilin University, Changchun, China Journal Journal of Intelligent and Fuzzy Systems Online ISSN 1875-8967 Print ISSN 1064-1246

Description: In this paper, we introduce the notions of coatom and comolecule of BL-algebras, also we state and prove some theorems which determines their properties. Finally we investigate some results in co-annihilators and verify the relationship between comolecules with prime filters, coatoms with hyperarchimedean and investigate ^ F for some types of filters. Content Type Journal Article Pages - DOI 10.3233/IFS-131002 Authors Mahdieh Abbasloo, Department of Mathematics, Science and Research Branch Islamic Azad University, Kerman, Iran Arsham Borumand Saeid, Department of Mathematics, Shahid Bahonar University of Kerman, Kerman, Iran Journal Journal of Intelligent and Fuzzy Systems Online ISSN 1875-8967 Print ISSN 1064-1246

Description: Ant colony optimization (ACO) inspires the foraging manner of real ants in digital habitat is a developed meta-heuristic algorithm in medical image processing. Magnetic resonance (MR) images usually contain irregular and complex structures. Applying ACO, the spatial information is exploited in image processing; however, ACO requires a supervisor to define reference food. Fuzzy c-means (FCM) is an unsupervised clustering algorithm used in medical image processing. Standard FCM seldom incorporates spatial information in image segmentation. This paper presents an Unsupervised ACO (UACO) developed by FCM which utilizes the benefits of two algorithms and overlaps their defects. UACO is unsupervised like FCM and incorporates spatial information the same way as ACO. Besides, elapsed time to define food source by FCM in UACO is less than that of an operator in ACO. Adding that, another novelty of the paper is to effectively update pheromone fields. Utilizing a Gaussian spatial function, proposed approach handles noise effects properly, and exploits spatial neighborhood information efficiently in image segmentation. Experimental results show that proposed hybrid UACO by the Gaussian spatial function preserves details of image and is less sensitive to noise. Content Type Journal Article Pages - DOI 10.3233/IFS-131008 Authors Abbas Biniaz, Faculty of Electrical Engineering, Computational Neuroscience Laboratory, Department of Biomedical Engineering, Sahand University of Technology, Tabriz, Iran Ataollah Abbasi, Faculty of Electrical Engineering, Computational Neuroscience Laboratory, Department of Biomedical Engineering, Sahand University of Technology, Tabriz, Iran Journal Journal of Intelligent and Fuzzy Systems Online ISSN 1875-8967 Print ISSN 1064-1246