University of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065410120130302Cover vol. 10, no. 1, February 20130272310.22111/ijfs.2013.2723ENJournal Article20161023https://ijfs.usb.ac.ir/article_2723_3ee3c7840b0dd11f70a6f651d5237cbc.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065410120130204A CONSTRAINED SOLID TSP IN FUZZY ENVIRONMENT:
TWO HEURISTIC APPROACHESA CONSTRAINED SOLID TSP IN FUZZY ENVIRONMENT:
TWO HEURISTIC APPROACHES12815310.22111/ijfs.2013.153ENChiranjitChangdarDepartment of Computer Science, Raja N.L. Khan Women's
College, Midnapore, Paschim- Medinipur, West Bengal, India-721102Manas KumarMaitiDepartment of Mathematics, Mahishadal Raj College, Mahishadal,
Purba- Medinipur, West Bengal, India-721628ManoranjanMaitiDepartment of Mathematics, Vidyasagar University, Midnapore,
Paschim- Medinipur, West Bengal, India-721102Journal Article20101204A solid travelling salesman problem (STSP) is a travelling salesman <br />problem (TSP) where the salesman visits all the cities only once in his <br />tour using di<br />erent conveyances to travel from one city to another. Costs <br />and environmental e<br />ect factors for travelling between the cities using di<br />erent <br />conveyances are di<br />erent. Goal of the problem is to nd a complete tour <br />with minimum cost that damages the environment least. An ant colony optimization <br />(ACO) algorithm is developed to solve the problem. Performance <br />of the algorithm for the problem is compared with another soft computing <br />algorithm, Genetic Algorithm(GA). Problems are solved with crisp as well as <br />fuzzy costs. For fuzzy cost and environmental e<br />ect factors, cost function as <br />well as environment constraints become fuzzy. As optimization of a fuzzy objective <br />function is not well de ned, fuzzy possibility approach is used to get <br />optimal decision. To test the eciency of the algorithm, the problem is solved <br />considering only one conveyance facility ignoring the environmental e<br />ect constraint, <br />i.e., a classical two dimensional TSP (taking standard data sets from <br />TSPLIB for solving the problem). Di<br />erent numerical examples are used for <br />illustration.https://ijfs.usb.ac.ir/article_153_100415578c754927aaf8d608b87dfdd1.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065410120130204A COGNITIVE STYLE AND AGGREGATION OPERATOR
MODEL: A LINGUISTIC APPROACH FOR CLASSIFICATION
AND SELECTION OF THE AGGREGATION OPERATORSA COGNITIVE STYLE AND AGGREGATION OPERATOR
MODEL: A LINGUISTIC APPROACH FOR CLASSIFICATION
AND SELECTION OF THE AGGREGATION OPERATORS296015410.22111/ijfs.2013.154ENKevin Kam FungYuenDepartment of Computer science and Software Engineering,
Xi'an Jiaotong-Liverpool University, 111 Ren Ai Road, Suzhou Industrial Park, Suzhou,
Jiangsu Province, 215123, P. R. ChinaJournal Article20110104Aggregation operators (AOs) have been studied by many schol- <br />ars. As many AOs are proposed, there is still lacking approach to classify the <br />categories of AO, and to select the appropriate AO within the AO candidates. <br />In this research, each AO can be regarded as a cognitive style or individual <br />di<br />erence. A Cognitive Style and Aggregation Operator (CSAO) model is pro- <br />posed to analyze the mapping relationship between the aggregation operators <br />and the cognitive styles represented by the decision attitudes. Four algorithms <br />are proposed for CSAO: CSAO-1, CSAO-2 and two selection strategies on the <br />basis of CSAO-1 and CSAO-2. The numerical examples illustrate how the <br />choice of the aggregation operators on the basis of the decision attitudes can <br />be determined by the selection strategies of CSAO-1 and CSAO-2. The CSAO <br />model can be applied to decision making systems with the selection problems <br />of the appropriate aggregation operators with consideration of the cognitive <br />styles of the decision makers.https://ijfs.usb.ac.ir/article_154_6135966bcbefde837de8dc2560d927ba.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065410120130204FUZZY GOAL PROGRAMMING TECHNIQUE TO SOLVE
MULTIOBJECTIVE TRANSPORTATION PROBLEMS WITH
SOME NON-LINEAR MEMBERSHIP FUNCTIONSFUZZY GOAL PROGRAMMING TECHNIQUE TO SOLVE
MULTIOBJECTIVE TRANSPORTATION PROBLEMS WITH
SOME NON-LINEAR MEMBERSHIP FUNCTIONS617415510.22111/ijfs.2013.155ENMaryamZangiabadiDepartment of Applied Mathematics, Faculty of Mathematical
Sciences, Shahrekord University, P.O. Box 115, Shahrekord, IranHamid RezaMalekiDepartment of Basic Sciences, Shiraz University of Technology,
Shiraz, IranJournal Article20110204The linear multiobjective transportation problem is a special type <br />of vector minimum problem in which constraints are all equality type and the <br />objectives are conicting in nature. This paper presents an application of <br />fuzzy goal programming to the linear multiobjective transportation problem. <br />In this paper, we use a special type of nonlinear (hyperbolic and exponential) <br />membership functions to solve multiobjective transportation problem. It gives <br />an optimal compromise solution. The obtained result has been compared with <br />the solution obtained by using a linear membership function. To illustrate the <br />methodology some numerical examples are presented.https://ijfs.usb.ac.ir/article_155_3287502ac100353886714e75cecddc84.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065410120130205MINIMIZATION OF DETERMINISTIC FINITE AUTOMATA
WITH VAGUE (FINAL) STATES AND INTUITIONISTIC
FUZZY (FINAL) STATESMINIMIZATION OF DETERMINISTIC FINITE AUTOMATA
WITH VAGUE (FINAL) STATES AND INTUITIONISTIC
FUZZY (FINAL) STATES758816410.22111/ijfs.2013.164ENAlkaChoubeyMathematics Department, Jaypee Institute of Information Technol-
ogy, A-10, Sector-62, Noida-201307 (U. P.), IndiaK. M.RaviDepartment of Mathematics, JSS Academy of Technical Education, C-
20/1, Sector-62, Noida-201301 (U. P), IndiaJournal Article20110205In this paper, relations among the membership values of gener- <br />alized fuzzy languages such as intuitionistic fuzzy language, interval-valued <br />fuzzy language and vague language are studied. It will aid in studying the <br />properties of one language when the properties of another are known. <br />Further, existence of a minimized nite automaton with vague ( final) states <br />for any vague regular language recognized by a nite automaton with vague <br />( final) states is shown in this paper. Finally, an ecient algorithm is given <br />for minimizing the nite automaton with vague ( final) states. Similarly, it can <br />be shown for intuitionistic fuzzy regular language. These may contribute to a <br />better understanding of the role of nite automaton with vague ( final) states <br />or the nite automaton with intuitionistic fuzzy ( final) states while studying <br />lexical analysis, decision making etc.https://ijfs.usb.ac.ir/article_164_8f88d3102db5acd9349513069a44355a.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065410120130205On the Diagram of One Type Modal Operators on Intuitionistic fuzzy
sets: Last expanding with $Z_{alpha ,beta }^{omega ,thetaOn the Diagram of One Type Modal Operators on Intuitionistic fuzzy
sets: Last expanding with $Z_{alpha ,beta }^{omega ,theta8910616610.22111/ijfs.2013.166ENG.Cuvalciogludepartment of mathematics, university of mersin, ciftlikkoy, 33016,
mersin turkeyJournal Article20110205Intuitionistic Fuzzy Modal Operator was defined by Atanassov in cite{at3}<br />in 1999. In 2001, cite{at4}, he introduced the generalization of these<br />modal operators. After this study, in 2004, Dencheva cite{dencheva} defined<br />second extension of these operators. In 2006, the third extension of these<br />was defined in cite{at6} by Atanassov. In 2007,cite{gc1}, the author<br />introduced a new operator over Intuitionistic Fuzzy Sets which is a<br />generalization of Atanassov's and Dencheva's operators. At the same year,<br />Atanassov defined an operator which is an extension of all the operators<br />defined until 2007. The diagram of One Type Modal Operators on<br />Intuitionistic Fuzzy Sets was introduced first in 2007 by Atanassov<br />cite{at10}. In 2008, Atanassov defined the most general operator and in<br />2010 the author expanded the diagram of One Type Modal Operators on<br />Intuitionistic Fuzzy Sets with the operator $Z_{alpha ,beta }^{omega }$.<br />Some relationships among these operators were studied by several researchers%<br />cite{at5}-cite{at8} cite{gc1}, cite{gc3}, cite{dencheva}- cite%<br />{narayanan}.<br />The aim of this paper is to expand the diagram of one type modal operators<br />over intuitionistic fuzzy sets . For this purpose, we defined a new modal<br />oparator $Z_{alpha ,beta }^{omega ,theta }$ over intuitionistic fuzzy<br />sets. It is shown that this oparator is the generalization of the operators<br />$Z_{alpha ,beta }^{omega },E_{alpha ,beta },boxplus _{alpha ,beta<br />},boxtimes _{alpha ,beta }.$https://ijfs.usb.ac.ir/article_166_54fe632cc30a351a943cae82a4dd7742.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065410120130206FUZZY INTEGRO-DIFFERENTIAL EQUATIONS: DISCRETE
SOLUTION AND ERROR ESTIMATIONFUZZY INTEGRO-DIFFERENTIAL EQUATIONS: DISCRETE
SOLUTION AND ERROR ESTIMATION10712216910.22111/ijfs.2013.169ENMasoumehZeinaliFaculty of mathematical sciences, University of Tabriz, Tabriz,
IranSedaghatShahmoradFaculty of mathematical sciences, University of Tabriz, Tabriz,
Iran0000-0002-2476-1176KamalMirniaFaculty of mathematical sciences, University of Tabriz, Tabriz, IranJournal Article20110806This paper investigates existence and uniqueness results for the <br />first order fuzzy integro-differential equations. Then numerical results and <br />error bound based on the left rectangular quadrature rule, trapezoidal rule <br />and a hybrid of them are obtained. Finally an example is given to illustrate <br />the performance of the methods.https://ijfs.usb.ac.ir/article_169_4d7ef7b69c85251841a56ba41099c819.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065410120130206SET-NORM EXHAUSTIVE SET MULTIFUNCTIONSSET-NORM EXHAUSTIVE SET MULTIFUNCTIONS12313417010.22111/ijfs.2013.170ENAncaCroitoruFaculty of Mathematics, "A.I. Cuza" University, Bd. Carol I, no 11,
Iasi-700506, RomaniaAlinaGavrilutFaculty of Mathematics, "A.I. Cuza" University, Bd. Carol I, no
11, Iasi-700506, RomaniaJournal Article20110206In this paper we present some properties of set-norm exhaustive <br />set multifunctions and also of atoms and pseudo-atoms of set multifunctions <br />taking values in the family of non-empty subsets of a commutative semigroup <br />with unity.https://ijfs.usb.ac.ir/article_170_2bb1c36480ee857421fd93fd71dde045.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065410120130206APPROXIMATE FIXED POINT IN FUZZY NORMED SPACES
FOR NONLINEAR MAPSAPPROXIMATE FIXED POINT IN FUZZY NORMED SPACES
FOR NONLINEAR MAPS13514217310.22111/ijfs.2013.173ENS. A. M.MohseniailhosseiniFaculty of Mathematics, Vali-e-Asr University of Raf-
senjan, Rafsenjan, IranH.MazaheriFaculty of Mathematics, Yazd University, Yazd, IranM. A.DehghanFaculty of Mathematics, Vali-e-Asr University of Rafsenjan, Raf-
senjan, IranJournal Article20110306We de ne approximate xed point in fuzzy norm spaces and prove <br />the existence theorems, we also consider approximate pair constructive map- <br />ping and show its relation with approximate fuzzy xed point.https://ijfs.usb.ac.ir/article_173_1b3c8fc3ea44800472a6b09a730cd34d.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065410120130206WEAK AND STRONG DUALITY THEOREMS FOR FUZZY
CONIC OPTIMIZATION PROBLEMSWEAK AND STRONG DUALITY THEOREMS FOR FUZZY
CONIC OPTIMIZATION PROBLEMS14315217410.22111/ijfs.2013.174ENB.FarhadiniaDepartment of Mathematics, Quchan Institute of Engineering and
Technology, Iran,0000000325808789A. V.KamyadDepartment of Mathematics, Ferdowsi University of Mashhad, Iran,Journal Article20110506The objective of this paper is to deal with the fuzzy conic program- <br />ming problems. The aim here is to derive weak and strong duality theorems <br />for a general fuzzy conic programming. Toward this end, The convexity-like <br />concept of fuzzy mappings is introduced and then a speci c ordering cone is <br />established based on the parameterized representation of fuzzy numbers. Un- <br />der this setting, duality theorems are extended from crisp conic optimization <br />problems to fuzzy ones.https://ijfs.usb.ac.ir/article_174_7ccb2ebf7e64971e3e0a4c7c1dd909f7.pdfUniversity of Sistan and BaluchestanIranian Journal of Fuzzy Systems1735-065410120130302Persian-translation vol. 10, no. 1, February 2013155163272410.22111/ijfs.2013.2724ENJournal Article20161023https://ijfs.usb.ac.ir/article_2724_70b945a70f7f7d14a5f622dc8b8f9e14.pdf