Fuzzy Hungarian Approach for Transportation Model

In this paper, a method is proposed to find the fuzzy optimal solution of fuzzy transportation model by representing all the parameters as trapezoidal fuzzy numbers. To illustrate the proposed method a fuzzy transportation problem is solved by using the proposed method and the results are obtained. The proposed method is easy to understand, and to apply for finding the fuzzy optimal solution of fuzzy transportation models in real life situations. However, we propose the method of fuzzy modified distribution for finding out the optimal solution for minimizing the cost of total fuzzy transportation. The advantages of the proposed method are also discussed

A New Approach to solve Fuzzy Transportation Problem for Trapezoidal Number

In this paper we are study on fuzzy transportation problem for industries to reduce the transportation cost of commodity from one source to another source. In this paper we are taking transportation cost, demand and supply all are in fuzzy trapezoidal number because the fuzzy number satisfy the condition of vagueness. Here we are using the propose algorithm to obtained the fuzzy optimal solution of fuzzy transportation problem with membership function. The solution procedure is illustrated with numerical example

Sustainable Development through Holistic Multi-Paradigmatic Integrated Modeling and Decision Making

Sustainability, sustainable development, and transformation is about balancing the economic, environmental and social aspects of organisations and their operations. Existing systems do not comprehensively support sustainable transformation nor do they allow decision makers to explore interrelationships and influences between the sustainability dimensions. This leads to silo based decision making where vision and strategies are not mapped to execution, and sustainability modelling processes are uncoordinated, lack holism, are biased and myopic. One of the critical challenges is the lack of processes and systems that allow the integration of models belonging to disparate paradigms in a holistic manner. To overcome these problems this research proposes a holistic, multi-paradigmatic, integrated modelling and decision making (HOMIMD) approach for sustainable development and transformation. We apply the HOMIMD processes, and requirements to a warehouse management problem and leverage optimization (AIMMS), systems dynamics (iThink), and data mining (SPSS Modeler) approaches, techniques, and systems to solve the problem

Fuzzy multi objective optimization: With reference to multi objective transportation problem

In this paper we present a review of the connection between modern era techniques & fuzzy multi objective optimization (FMOO) to deal with its shortcoming and FMOO used in transportation problem. Multi objective optimization represents an interest area of research since most real life problem have a set of conflict objectives. MOO has its root in late nineteenth century welfare economics, in the works of Edge worth & Pareto. But due to some shortcoming faces, researchers attract to FMOO and they use modern era technique like artificial intelligence. Finally we develop a fuzzy linear programming method for solving the transportation problem with fuzzy goals, available supply & forecast demand and showing a frame for fuzzy multi objective transportation problem (FMOTP) solution.           &nbsp

Fuzzy Programming With Quadratic Membership Functions For Multi-objective Transportation Problem

<p>In the present paper, a fuzzy programming model with quadratic membership functions has been developed for the solution of a Multi-Objective Transportation problem. In literature, several fuzzy programming approaches exist with various types of membership functions such as linear, exponential, hyperbolic etc. These membership functions are defined, by taking the lower and upper values of the objective functions into account.  In some cases, these methods fail to obtain an integer compromise optimal solution. In the present method, two coefficients of the quadratic membership functions are determined by the lower and upper values of the objective functions. The other coefficient is taken as a variable in the fuzzy programming approach. This means that the membership curve is fixed at the two end points and set free in between. Application of the method on numerical examples proved that the approach could generate integer compromise optimal solutions.  </p

Multi-objective Optimization Proposal with Fuzzy Coefficients in both Constraints and Objective Functions.

Propuesta de optimización multiobjetivo con coeficientes difusos en restricciones y en funciones objetivo.AbstractFuzzy sets, and more specifically, fuzzy numbers can be a very suitable way to include uncertainty within the formulation and solution of linear problems with multiple goals. Goals in a decision problem do not need to be either maximized, or minimized, as in classical mathematical programming, but they are substituted by aspiration levels, and they need to be met in order to satisfy the decision-maker. Experience shows that it is easier for the decision-maker to formulate both objectives and constraints with fuzzy coefficients, rather than specify a defined quantity for the matrices A, b or g. This paper shows the versatility of a methodology that solves multi-objective linear problems, formulated with fuzzy coefficients. This conception becomes an alternative in contrast with the hard methodologies predominant in Operations Research, since the fuzzy approach allows the decision-maker to make uncertain assumptions both for the formulation and solution of optimization problems.Keywords: Fuzzy logic, multi-criteria analysis, triangular fuzzy numbers.ResumenLos conjuntos difusos y específicamente los números difusos constituyen una manera efectiva de incluir la incertidumbre en la formulación y solución de problemas lineales de optimización multiobjetivo. Las metas en un problema de decisión no necesitan ser maximizadas ni minimizadas, como ocurre en las herramientas clásicas de programación matemática, sino que se pueden sustituir por niveles de aspiración, las cuales constituyen las expectativas para un decisor. La experiencia demuestra que es más fácil para el decisor formular los objetivos y las restricciones en un problema con coeficientes difusos, en vez de simplemente especificar un número concreto en las matrices A, b ó g. Este artículo presenta la versatilidad de una formulación metodológica que permite resolver problemas multiobjetivo de tipo lineal, los cuales son formulados con coeficientes difusos. Esta concepción constituye una alternativa a las metodologías duras que dominan la investigación de operaciones, dado que la aproximación difusa permite que los decisores realicen presunciones inciertas en la formulación y solución en los problemas de optimización.Palabras Clave: Lógica difusa, análisis multiobjetivo, números triangulares difusos

Modified Approach for Optimization of Real Life Transportation Problem in Neutrosophic Environment

To the best of our knowledge, there is only one approach for solving neutrosophic cost minimization transportation problems. Since neutrosophic transportation problems are a new area of research, other researchers may be attracted to extend this approach for solving other types of neutrosophic transportation problems like neutrosophic solid transportation problems, neutrosophic time minimization transportation problems, neutrosophic transshipment problems, and so on. However, after a deep study of the existing approach, it is noticed that a mathematical incorrect assumption has been used in these existing approaches; therefore there is a need to modify these existing approaches. Keeping the same in mind, in this paper, the existing approach is modified. Furthermore, the exact results of some existing transportation problems are obtained by the modified approach