By S. H. Nasseri, Z. Alizadeh, B. Khabiri (auth.), Bing-Yuan Cao, Xiang-Jun Xie (eds.)
“Fuzzy Engineering and Operations examine” is the edited final result of the fifth overseas convention on Fuzzy info and Engineering (ICFIE2011) held in the course of Oct. 15-17, 2011 in Chengdu, China and by way of the first educational convention in institution of Guangdong Province Operations learn Society (GDORSC) hung on Oct. 20, 2011 in Guangzhou, China. The fifth ICFIE2011, equipped at the good fortune of past meetings, and the GDORC, first held, are significant Symposiums, respectively, for scientists, engineers practitioners and Operation examine (OR) researchers featuring their up-to-date effects, advancements and purposes in all parts of fuzzy details and engineering and OR. It goals to reinforce family among examine laboratories and universities, and to create a first-rate symposium for international scientists in Fuzziology and OR fields. The booklet includes sixty two papers and is split into 5 major components: “Fuzzy Optimization, common sense and Information”, “The mathematical concept of Fuzzy Systems”, “Fuzzy Engineering purposes and tender Computing Methods”, “OR and Fuzziology” and “Guess and Review”.
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Duality results and a dual simplex method for linear programming problems with trapezoidal fuzzy variables. Fuzzy Sets and Systems 158, 1961–1978 (2007) 12. : Fuzzy primal simplex algorithms for solving fuzzy linear programming problems. Iranian Journal of Operational Research 2, 68–84 (2009) A New Approach to Duality in Fuzzy Linear Programming 29 13. : Linear programming with fuzzy variables. Fuzzy Sets and Systems 109, 21–33 (2000) 14. : A fuzzy primal simplex algorithm and its application for solving the flexible linear programming problems.
This is midpoint of interval numbers, or position i =1 coefficient of interval numbers. That is, midpoint of interval numbers is measured to the size of target, it make fuzzy target be crisp. 4 Numerical Examples The following gives a numerical example for illustrating the interval number fuzzy portfolio selection model with liquidity constraints and the method to solve the linear programming. The data is mainly taken from the literature 11 and 13, see also Table 1, Table 2 and Table 3. Table 1.
Sensitivity analysis in fuzzy linear programming. Fuzzy Sets and Systems 1, 269–281 (1978) 7. : Fuzzy goal programming: Complementary slackness conditions and computational schemes. Applied Mathematics and Computation 179, 506–522 (2006) 8. : Fully fuzzified linear programming, solution and duality. Journal of Intelligent and Fuzzy Systems 17, 253– 261 (2006) 9. : Satisficing solutions and duality in interval and fuzzy linear programming. Fuzzy Sets and Systems 135, 151–177 (2003) 10. : Duality in fuzzy number linear programming by use of a certain linear ranking function.