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2019•Journal of Informatics and Mathematical SciencesOpen access

Solving Multi Objective Linear Fractional Programming Problem Under Uncertainty via Robust Optimization Approach

Moslem Ganji, Mansour Saraj

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Abstract

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 (RC) formulations is studied. We use box uncertainty set for MOLFP problem and propose an approach to derive its corresponding RC formulation by reducing it into a single objective programming problem. It is shown that the corresponding RC formulation of MOLFP problem under box uncertainty set is a  Linear Programming (LP) problem. A numerical example is worked out to illustrate the methodology and proposed approach.

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What this paper is about

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 (RC) formulations is studied. We use box uncertainty set for MOLFP problem and propose an approach to derive its corresponding RC formulation by reducing it into a single objective programming problem. It is shown that the corresponding RC formulation of MOLFP problem under box uncertainty set is a  Linear Programming (LP) problem. A numerical example is worked out to illustrate the methodology and proposed approach.

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Available abstract

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 (RC) formulations is studied. We use box uncertainty set for MOLFP problem and propose an approach to derive its corresponding RC formulation by reducing it into a single objective programming problem. It is shown that the corresponding RC formulation of MOLFP problem under box uncertainty set is a  Linear Programming (LP) problem. A numerical example is worked out to illustrate the methodology and proposed approach.

Key concepts: Fractional programming, Linear programming, Linear-fractional programming, Mathematical optimization, Robust optimization, Mathematics, Set (abstract data type), Optimization problem

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