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The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.
The journal will publish original articles on current and potential applications, case studies, and education in intelligent systems, fuzzy systems, and web-based systems for engineering and other technical fields in science and technology. The journal focuses on the disciplines of computer science, electrical engineering, manufacturing engineering, industrial engineering, chemical engineering, mechanical engineering, civil engineering, engineering management, bioengineering, and biomedical engineering. The scope of the journal also includes developing technologies in mathematics, operations research, technology management, the hard and soft sciences, and technical, social and environmental issues.
Authors: Soni, Hardik N. | Sarkar, Biswajit | Joshi, Manisha
Article Type: Research Article
Abstract: This paper presents a continuous review inventory model with backorders and lost sales with fuzzy demand and learning considerations. The imprecision in demand is characterized by triangular fuzzy numbers. The triangular fuzzy numbers, counts upon lead time, are used to construct fuzzy lead time demand. It is assumed that the imprecision captured by these fuzzy numbers reduce with time because of learning effect. This implies that the decision maker gathers information about the inventory system and builds up knowledge from the previous shipments. Learning process occurs in setting and estimating the fuzzy parameters to reduce errors and costs. Under these …considerations, the proposed model offers a policy and a solution algorithm to calculate the number of orders and reorder level such that the total annual cost attains a minimum value. The results of the proposed model are compared with the continuous review inventory system with fuzzy demand with or without learning effect. It is shown that learning effect in fuzziness reduces the ambiguity associated with the decision making process. Finally, numerical examples are provided to illustrate the importance of using learning in fuzzy model. The convexity of the total cost function is also proved. Show more
Keywords: Uncertainty, continuous review inventory model, possibilistic mean value, learning in fuzziness
DOI: 10.3233/JIFS-16372
Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2595-2608, 2017
Authors: Wang, Fengxiao
Article Type: Research Article
Abstract: In this paper, the concepts of interval-valued fuzzy ideals in B-algebras are introduced and investigated some of their properties. The homomorphic inverse image of interval-valued intuitionistic fuzzy ideals are studied. The intersection and Cartesian product of interval-valued fuzzy ideals in B-algebras are discussed.
Keywords: B-algebra, interval-valued fuzzy ideals, homomorphic image, intersection
DOI: 10.3233/JIFS-17053
Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2609-2615, 2017
Authors: Guo, Xiaobin | Han, Yanlong
Article Type: Research Article
Abstract: The paper considers the general dual fuzzy matrix equation A X ˜ + B ˜ = C X ˜ + D ˜ in a complete matrix method. We firstly introduce the fuzzy matrix and its operation with crisp number. Then we convert the dual fuzzy matrix equation to a model which is a crisp function matrix equation. The fuzzy approximate solution of dual fuzzy matrix equation is obtained by solving the model. The existence condition of the strong fuzzy solution is also discussed. In addition, we investigate the LR dual fuzzy …matrix equation by the same way. Finally, some examples are given to illustrate our proposed method. Show more
Keywords: Fuzzy numbers, fuzzy numbers matrix, dual fuzzy matrix equations, fuzzy approximate solutions
DOI: 10.3233/JIFS-17072
Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2617-2629, 2017
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