[PDF] Top 20 A 0-1 Random Fuzzy Programming Problem Based on the Degree of Necessity and the Efficient Solution Method

... mathematical programming problems involving 0-1 programming problems, the coefficients of objective functions or constraints are assumed to be completely known and dealt with constant ... See full document

... speaking, solution methods of 0-1 programming problems mainly divides into two types; (a) strict solution methods such as dynamic programming and branch-bound method, (b) ... See full document

... location problem of competitive facilities, ...as fuzzy random variables, the location problem can be formulated as a fuzzy random programming ...the fuzzy ... See full document

... location problem of competitive facilities, ...as fuzzy random variables, the location problem can be formulated as a fuzzy random pro- gramming ...the fuzzy random ... See full document

... world problem due to the ambiguity, uncertainty, imprecise, and vagueness of the data, and is considered as the main concern of modern companies in highly competitive ...integer programming model for ... See full document

... mathematical programming models is crucial to obtain the feasible and proper ...mathematical programming model which treats fuzzy random data, and further treats ambiguity and fuzziness in the ... See full document

... transportation problem in the fuzzy sense expressed in linear programming ...used fuzzy numbers of the type L-L to fuzzify cost coefficients in the objective function and  -cut to express the ... See full document

... presented fuzzy goal pro- gramming (FGP) algorithm for solving decen- tralised bi-level multi objective (DBL-MOP) problems with a single decision maker at the up- per level and multiple decision makers at the ... See full document

... mathematical programming solutions for multi-criteria decision making problem, conventionally, the crisp values are used in the formulation of the problem ...distribution, fuzzy numbers, and ... See full document

... the fuzzy MOLP problem with fuzzy technological coefficients and ...the problem based on the proposed method introduced by Gasimov and Yenimez ...the Fuzzy MOLP ... See full document

... the fuzzy random portfolio selection problem where the asset returns are represented by fuzzy random ...the necessity-based model, fuzzy random variables ... See full document

... Optimal solution of a fully fuzzy linear fractional programming problem by using graded mean integration representation method " Applications and Applied Mathematics, vol 10 , ... See full document

... the fuzzy concept has been ...linear programming problem formulation. Further fuzzy constraint coefficient in linear programming was considered by Fang and ...classified based on ... See full document

... fractional programming problem by using Zadeh extension ...solving Fuzzy trilevel Quadratic Fractional Programming Problems ...This method works according with three characteristic ... See full document

... the problem are usually defined in an uncertain ...known. Fuzzy sets theory, introduced by Zadeh [24] make this possible. Fuzzy numerical data can be represented by means of fuzzy subsets of ... See full document

... Let the solution of FGP model (3) is ( U V , V V , … . , : V ) and the value of each objective function a ® at this point is a ® V , now we will find membership functions as ª ¯ about ( U V , V V , … . , : V ) ... See full document

... Step 5. If some nonbasic variable at x k does not generate feasible non basic solution to P1 when alter marginally discard it. Oterwise determine the DM’S preferred in the direction of trade offs between the ... See full document

... In the design problem of the structure i.e lightest weight of the structure and minimum deflection of the loaded joint that satisfies all stress constraints in members of the structure .In truss structure ... See full document

... regression problem in the presence of both random and fuzzy variables [1]; Renewal processes where inter-arri- val times are only known as subjective categories of the form; almost 3 hours, ... See full document

... The matrix D is assumed symmetric and negative defi- nite. This means that f(X) is strictly concave. The con- straints are linear thus a convex solution space is guaran- teed. Any maximization quadratic model can ... See full document