the fuzzy linear regression model with fuzzy input-output data andcrisp coefficients is studied in this paper. a linear programmingmodel based on goal programming is proposed to calculate theregression coefficients. in contrast with most of the previous works, theproposed model takes into account the centers of fuzzy data as animportant feature as well as their spreads in the procedure ofconstr...

in this paper, a mathematical method is proposed to formulate a generalized ordering problem. this model is formed as a linear optimization model in which some variables are binary. the constraints of the problem have been analyzed with the emphasis on the assessment of their importance in the formulation. on the one hand, these constraints enforce conditions on an arbitrary subgraph and then g...

In this paper, we present a polynomial-sized linear programming formulation of the Traveling Salesman Problem (TSP). The proposed linear program is a network flow-based model. Numerical implementation issues and results are discussed. KeyWords: Linear Programming; Network Optimization; Integer Programming; Traveling Salesman Problem; Combinatorial Optimization; Scheduling; Sequencing.

Computer programming today is far too dependent on one particular natural language, namely English. Mathematics is not dependent on English, and programming should not be, either. In order to eliminate the dependence of programming on English, we have constructed a programming language in which the keywords are replaced by symbols available on standard keyboards. Each of these symbols is chosen...

-A neural network approach for solving fuzzy linear programming problems is proposed in which fuzzy concepts are not used. This approach is totally based on the level-sum method introduced Pandian [11]. The nearest optimal solution of the fuzzy linear programming original problem can be obtained by the proposed approach. The large scale fuzzy linear programming problems can be solved efficientl...

In this paper, possibilistic linear programming problems are investigated. After reviewing relations among conjunction and implication functions, necessity fractile optimization models with various implication functions are applied to the possibilistic linear problems. We show that the necessity fractile optimization models are reduced to semi-infinite linear programming problems. A simple nume...

bilevel linear programming  is a decision making problem with a two-level decentralized organization. the textquotedblleft leadertextquotedblright~ is in the upper level and the textquotedblleft followertextquotedblright, in the lower. making a decision at one level affects that at the other one. in this paper, bilevel linear programming  with inexact parameters has been studied and a method is...

multiple objective programming (mop) problems have become famous among many researchers due to more practical and realistic implementations. there have been a lot of methods proposed especially during the past four decades. in this paper, we develop a new algorithm based on a new approach to solve mop problems by starting from a utopian point (which is usually infeasible) and moving towards the...

The concept of duality plays an important role in optimization theory .In this paper, a new method is proposed to find the fuzzy optimal solution of fully fuzzy linear programming problems using breaking point and duality theory. By using the proposed method the fuzzy optimal solution of fully fuzzy linear programming problem with inequality constraints has been obtained. To illustrate the prop...