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Showing 5 results for Fuzzy Number
Jain,
Volume 2, Issue 1 (4-2010)
Abstract
The fuzzy approach has undergone a profound structural transformation in the past few decades. Numerous studies have been undertaken to explain fuzzy approach for linear and nonlinear programs. While, the findings in earlier studies have been conflicting, recent studies of competitive situations indicate that fractional programming problem has a positive impact on comparative scenario. We propose one of the best interval approximations, close interval approximation of piecewise quadratic fuzzy numbers for solving fuzzy number fractional programming problem without converting it to a crisp problem. A new form of simplex method is introduced here for solving fuzzy number fractional programming problem using fuzzy arithmetic. The fuzzy analogue of some important theorems of fuzzy fractional programming problem proved. A fuzzy fractional programming problem is worked out as an example to illustrate the proposed method.
Babak Khabiri, Majid Iranmanesh,
Volume 14, Issue 1 (6-2023)
Abstract
A transportation problem involving three constraints: source, destination, and conveyance, where all parameters of the problem are fuzzy is called Fully Fuzzy Solid Transportation Problem (FFSTP). In this paper, a new method is proposed to find an optimal solution of an unbalanced FFSTP which the fuzzy numbers are considered to be k-scale trapezoidal fuzzy numbers. The k-scale trapezoidal fuzzy numbers are a generalization of symmetric trapezoidal fuzzy numbers which are considered recently in the literature. In this method, using a new ranking method, we transform the unbalanced FFSTP into a crisp linear programming formulation and find a fuzzy optimal solution for it. The considered model is not necessary balanced and introduced method will solve that without convert it to a balanced model. The advantages of the proposed method are also discussed.
Ali Abbass Hadi, Seyed Hadi Nasseri,
Volume 15, Issue 2 (12-2024)
Abstract
In this work, we consider a multi-objective minimal cost flow (MMCF) problem where there are several commodities to transport from sources to destinations and there is more than one conveyance for those transporting. We also assume that in each conveyance, there are distinct capacities for each commodity. The obtained model is not necessary balanced, and we introduced a method to solve this model without converting it to a balanced model. Some advantages of the proposed method is discussed.
Roghayeh Yaser, Hadi Nasseri,
Volume 15, Issue 2 (12-2024)
Abstract
Supplier selection is one of the main discussions in the Supply Chain. The issue of assigning purchase orders to suppliers that act differently in terms of quality, cast, services, etc. criteria is one of the significant concerns of purchase managers in the supply chain. To adopt an optimal decision in this regard is related to a multi-objective problem that the objectives are contradicting each other and have different importance and priority depending on the location. In practice, the existence of kind of ambiguity in explaining the information related to the problem constraints and complicated. In this regard, the emergence of Fuzzy set theory as a tool to describe such conditions besides presenting question model realistically can help to solve such problems well. Despite the importance of the model with the mentioned structure, unfortunately, few original works have been done in this field. As a result, in this paper, in addition to presenting a new multi-objective Fuzzy model being modelled based on assigning purchase order to suppliers in a supply chain a solution method is introduced based on using Fuzzy linear programming. To clarify solution process modelling and description, a case study is included related to selecting flour supplier for providing industrial bread of Khoshkar factory. The proposed model includes four objective functions:
- Aggregate costs of minimizing type,
- Services of maximizing type (such as packing, being faithful to promise, factory heath, discount, correct transportation, good relationships, honestly, etc.),
- Flour useful survival of maximizing type (regarding monthly flour buying by the factory),
- The purchased flour quality of maximizing type (concerning product type).
Especially in the solution process, a method is determined based on setting weight for each of the objectives concerning the major factory stockholders.
Sepideh Taghikhani, Fahimeh Baroughi, Behrooz Alizadeh,
Volume 15, Issue 2 (12-2024)
Abstract
The backup 2-median location problem on a tree T is to deploy two servers at the vertices such that the expected sum of distances from all vertices to the set of functioning servers is minimum. In this paper, we investigate the backup 2-median location problem on tree networks with trapezoidal interval type-2 fuzzy weights. We first, present a new method for comparing generalized trapezoidal fuzzy numbers and then develop it for trapezoidal interval type-2 fuzzy numbers. Then numerical examples are given to compare the proposed methods with other existing methods. Finally, we apply our ranking method to solve the the backup 2-median location problem on a tree network with trapezoidal interval type-2 fuzzy weights.
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