In the present paper, the study of fully fuzzy linear fractional programming problem (FFLFPP) using graded mean integration representation method is discussed where all the parameters and variables are characterized by trapezoidal fuzzy numbers. A computational algorithm has been presented to obtain an optimal solution by applying simplex method. To demonstrate the applicability of the proposed...

We present a projective generalization of closed sets, called complete projective embeddings, which allows us to inscribe H-polyhedra in quadrics efficiently. Essentially, the complete projective embedding of a closed convex set P ⊆ K is a double cone in K. We show that complete projective embeddings of polyhedral sets are of particular interest and already occurred in the theory of linear frac...

The decision makers, in the sectors like financial and corporate planning, production planning, marketing and media selection, university planning and student admissions, health care and hospital planning, etc. often face problems to take decisions that optimize department/equity ratio, profit/cost, inventory/sales, actual cost/standard cost, output/employee, student/cost, nurse/patient ratio e...

This paper presents the Facet Generation Procedure (FGP) for solving 0/1 integer programs. The FGP seeks to identify a hyperplane that represents a facet of an underlying polytope to cut off the fractional solution to the linear programming relaxation of the integer programming problem. A set of standard problems is used to provide insight into the computational characteristics of the procedure.

Structural redundancies in mathematical programming models are nothing uncommon and nonlinear programming problems are no exception. Over the past few decades numerous papers have been written on redundancy. Redundancy in constraints and variables are usually studied in a class of mathematical programming problems. However, main emphasis has so far been given only to linear programming problems...

This paper presents a branch-and-bound algorithm for globally solving a wide class of generalized linear fractional programming problems (GLFP). This class includes such problems as: minimizing a sum, or error for product of a finite number of ratios of linear functions, linear multiplicative programming, polynomial programming, etc. – over nonconvex feasible region. First a problem (Q) is deri...

Abstract: This paper introduces a new approach to H2 robust filtering design for continuoustime LTI systems subject to linear fractional parameter uncertainty representation. The novelty consists on the determination of a performance certificate, in terms of the gap between lower and upper bounds of a minimax programming problem which defines the optimal robust equilibrium cost. The calculation...

This paper presents an interval valued goal programming approach for solving multiobjective fractional programming problems. In the model formulation of the problem, the interval-valued system constraints are converted in to equivalent crisp system. The interval valued fractional objective goals are transformed into linear goals by employing the iterative parametric method which is an extension...

This paper presents a neural network for solving non-linear minimax multiobjective fractional programming problem subject to nonlinear inequality constraints. Neural model is designed for optimization with constraints condition. Methodology is based on the lagrange multiplier with saddle point optimization.