Abstract
Transportation theory is the name given to the study of optimal transportation (OT) and resource allocation in mathematics and economics. In any discipline of science and technology, ...engineering, medicine, and management, uncertainty plays a critical role. Fuzzy Mathematics (FM) and fuzzy logic (FL) are used in Artificial Intelligence (AI) to process natural language and are frequently employed in decision making (DM). In this paper, using three ranking function to treat the fuzzy transportation model, two of them are Yager and Maleki ranking functions and the other is proposal and suggest depend up on of Yager ranking function based on trapezoidal fuzzy membership function when the total demand, cost of transportation, and the total amount of product (supply) are fuzzy, then the fuzzy model shrinkage to traditional or crisp model. Finally solving these models to the real data that we got it from The General Company for Food Products Abo ghreeb / Iraq.
In many applications such as production, planning, the decision maker is important in optimizing an objective function that has fuzzy ratio two functions which can be handed using fuzzy fractional ...programming problem technique. A special class of optimization technique named fuzzy fractional programming problem is considered in this work when the coefficients of objective function are fuzzy. New ranking function is proposed and used to convert the data of the fuzzy fractional programming problem from fuzzy number to crisp number so that the shortcoming when treating the original fuzzy problem can be avoided. Here a novel ranking function approach of ordinary fuzzy numbers is adopted for ranking of triangular fuzzy numbers with simpler and easier calculations as well as shortening in the procedures. The fuzzy fractional programming problem is the first reduced to a fractional programming problem and then solved with the technique to obtain the optimal solution. It has a power to give a best solution for supporting the solution theory proposed in this work, some numerical fuzzy fractional programming problem are included to ensure the advantage, efficiency and accuracy of the suggested algorithm. In addition, this research paper describes a comparison between our optimal solutions with other existing solutions for inequalities constrains fuzzy fractional program.
Graph is a tool that can be used to simplify and solve network problems. Domination is a typical network problem that graph theory is well suited for. A subset of nodes in any network is called ...dominating if every node is contained in this subset, or is connected to a node in it via an edge. Because of the importance of domination in different areas, variant types of domination have been introduced according to the purpose they are used for. In this paper, two domination parameters the first is the restrained and the second is secure domination have been chosn. The secure domination, and some types of restrained domination in one type of trees is called complete ary tree are determined.
In this paper two ranking functions are employed to treat the fuzzy multiple objective (FMO) programming model, then using two kinds of membership function, the first one is trapezoidal fuzzy (TF) ...ordinary membership function, the second one is trapezoidal fuzzy weighted membership function. When the objective function is fuzzy, then should transform and shrinkage the fuzzy model to traditional model, finally solving these models to know which one is better
The most important one advantages of the operation research (OR) theory is displayed of this paper for tackling multi-objective function programming problems (MOFPP). In this study, we present an ...approach for multi-objective fractional programming problems (MOFrPP) using fuzzy numbers (FN) coefficients in the objective functions (OF). The objective functions' (OF) parameters are all considered to be fuzzy triangular fuzzy numbers (FTrFN). This problem's multi-objective function (MOF) case was resolved by transforming the MOF to a linear programming problem (LnPP) that could be resolved using the simplex method (SM). The problem is being solved using algorithms. Then the value is compared with a result, which obtained by simplex method (SM). These techniques are illustrated with numerical examples (NE). This study shows the reliability of our methods and their utility to this specific set of multi-objective functions (MOF).
In this work, we suggested a novel algorithm to computation the optimal Solution for the fuzzy octagonal fractional programming problems (FOFPP) were transformed to crisp value (CV), through the ...ranking function (RF), and then solved a crisp value by graphical method. Finally, numerical examples are presented to display the efficacy of the computational procedure.
We propose a development ranking function (RF) to solve project - scheduling problems (PSP) in a foggy environment. The development command works on fuzzy numbers (FN) and this is done by converting ...the fuzzy parameters to an explicit value and applying the critical path method (CPM) to obtain the solution described in the proposed algorithm. A clear definition of the time limit will aid in the successful implementation of CPM, there is often confusion regarding the length of the process leading to the development of a critical path method (CPM) system. The example and approach strongly suggest that the proposed method is efficient and gives us the critical path (CP) and identifies sensitive activities as well. The results show that the use of the development ranking function (DRF) is better, more efficient, and accurate than the other ranking function (RF) by calculating the hours of the project completion.
Many types of ambiguous numbers have been studied in many mathematical fields. Two of these types, the obscure number hexagonal and octagonal are widely used, especially in mathematical ...programming. A linear fuzzy number (LFN), which generalizes these two types, is presented in this paper. Based on the definition of the order function by the total value, two ranking function for this linear fuzzy number is used. Arithmetic operations with their properties are entered on ambiguous numbers as a special case. It also turns out that the operations proposed on LFN are acceptable generalizations of conventional arithmetic operations on real numbers.
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