here‎, ‎we aim to develop a new algorithm for solving a multiobjective linear programming problem‎. ‎the algorithm is to obtain a solution which approximately meets the decision maker's preferences‎. ‎it is proved that the proposed algorithm always converges to a weak efficient solution and at times converges to an efficient solution‎. ‎numerical examples and a simulation study are used to...

This paper deals with a nonlinear multiobjective semi-infinite programming problem involving generalized (C,α, ρ, d)-convex functions. We obtain sufficient optimality conditions and formulate the Mond-Weirtype dual model for the nonlinear multiobjective semi-infinite programming problem. We also establish weak, strong and strict converse duality theorems relating the problem and the dual problem.

In this paper, we consider nonsmooth multiobjective fractional programming problems involving locally Lipschitz functions. We introduce the property of generalized invexity for fractional function. We present necessary optimality conditions, sufficient optimality conditions and duality relations for nonsmooth multiobjective fractional programming problems, which is for a weakly efficient soluti...

Two major approaches to deal with randomness or impression involved in mathematical programming problems have been developed. The one is called stochastic programming, and the other is called fuzzy programming. In this paper, we focus on multiobjective integer programming problems involving random variable coefficients in constraints. Using the concept of simple recourse, such multiobjective st...

Convex multiobjective programming problems and multiplicative programming problems have important applications in areas such as finance, economics, bond portfolio optimization, engineering, and other fields. This paper presents a quite easy algorithm for generating a number of efficient outcome solutions for convex multiobjective programming problems. As an application, we propose an outer appr...

Here‎, ‎we aim to develop a new algorithm for solving a multiobjective linear programming problem‎. ‎The algorithm is to obtain a solution which approximately meets the decision maker's preferences‎. ‎It is proved that the proposed algorithm always converges to a weak efficient solution and at times converges to an efficient solution‎. ‎Numerical examples and a simulation study are used to illu...

in this paper, we introduce a satisfaction function (sf) to compare interval values on the basis oftseng and klein’s idea. the sf estimates the degree to which arithmetic comparisons between two intervalvalues are satisfied. then, we define two other functions called lower and upper sf based on the sf. weapply these functions in order to present a new interpretation of inequality constraints wi...

This paper discusses an Interval Quadratic Programming (IQP) problem, where the constraints coefficients and the right-hand sides are represented by interval data. First, the focus is on a common method for solving Interval Linear Programming problem. Then the idea is extended to the IQP problem. Based on this method each IQP problem is reduced to two classical Quadratic Programming (QP) proble...