The present paper evaluates the Sen's Multi-Objective Programming (MOP) method for
solving multi-objective optimization problems. The method has been successfully used in …

There are many techniques for solving Multi-Objective Optimization (MOO) problems. Goal
programming, Weighted sum method, lexicographic method, and Ɛ-constraints method are …

Several scalarizing techniques are used for solving multi-objective optimization (MOO)
problems. Most of these scalarizing techniques were found inefficient in obtaining an …

This paper presents an advanced optimal average of maximin & minimax technique to solve
multi-objective quadratic fractional programming problem (MOQFPP) to single objective …

In this article, a Multi Objective Linear Fractional Programming (MOLFP) problem with
uncertain data in the objective function and the relationship between its Robust Counterpart …

Multi-objective optimization problem (MOOP) is an important class of optimization problem
that ensures users to model a large variety of real world applications. In this paper an …

In this paper, we used an Interactive Techniques and New Geometric Average Techniques
to solve multi-objective linear fractional programming problems (MOLFPP), and algorithms …

An error in the estimation of multiobjective function has been pointed out by Dr. Sanjay and
Dr. Adarsh in a research paper on Multiobjective Optimization (MOO) problems. The …

The paper evaluates the newly proposed averaging techniques for solving multi-objective
optimization problems. Arithmetic mean, Harmonic mean, Geometric mean and many more …

Multi-objective linear programming can be generated from fuzzy linear programming. This
multi-objective linear programming can be further converted to single objective linear …