A Multi-Level Fractional Programming Problem with Stochastic Parameters in Constraint

This paper proposes an approach where it can be applied to the optimization decision making problems under various uncertainties and solves a multi-level fractional programming problem (MLFPP) involving stochastic parameters coefficient in which some dependent variables are to be constrained with a...

Full description

Saved in:
Bibliographic Details
Published inInternational journal of engineering innovations and research Vol. 3; no. 5; p. 650
Main Authors Helmy, Y M, Emam, O E, Abdelwahab, A M
Format Journal Article
LanguageEnglish
Published 01.09.2014
Subjects
Dependent variables
Mathematical models
Optimization
Polynomials
Probability theory
Programming
Stochasticity
Taylor series
Online AccessGet full text

Cover

More Information
Summary:This paper proposes an approach where it can be applied to the optimization decision making problems under various uncertainties and solves a multi-level fractional programming problem (MLFPP) involving stochastic parameters coefficient in which some dependent variables are to be constrained with a predefined probability. Such problems are called optimization under chance constraints. In this paper, the first phase of the solution approach, the authors convert the probabilistic nature (stochastic) of this problem in the constraints into a multi-level fractional programming problem (MLFPP). Then, in the second phase, they use the 1St order Taylor series polynomial series to convert (MLFPP) into a multi-level linear programming problem (MLFPP) for generating a compromise solution for this problem. In addition, a numerical example is provided to demonstrate the correctness of the proposed solution.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
content type line 23
ObjectType-Feature-2
ISSN:2277-5668