Showing 4 results for Khalifa
Hamiden Abdelwahed Khalifa,
Volume 29, Issue 4 (IJIEPR 2018)
Abstract
This paper deals with multi- objective nonlinear programming problem having rough intervals in the constraints. The problem is approached by taking maximum value range and minimum value range inequalities as constraints conditions, reduces it into two classical multi-objective nonlinear programming problems, called lower and upper approximation problems. All of the lower and upper approximation problems may be solved using the weighting method, where an optimal rough interval solution is obtained. The stability set of the first kind corresponding to the optimal rough interval solution is determined. An illustrative numerical example is given to clarify the obtained results.
Hamiden Abd Elwahed Khalifa, El- Saed Ebrahim Ammar,
Volume 30, Issue 1 (IJIEPR 2019)
Abstract
Fully fuzzy linear programming is applied to water resources management due to its close connection with human life, which is considered to be of great importance. This paper investigates the decision-making concerning water resources management under uncertainty based on two-stage stochastic fuzzy linear programming. A solution method for solving the problem with fuzziness in relations is suggested to prove its applicability. The purpose of the method is to generate a set of solutions for water resources planning that helps the decision-maker make a tradeoff between economic efficiency and risk violation of the constraints. Finally, a numerical example is given and is approached by the proposed method.
Hamiden Khalifa, E. E. Ammar,
Volume 31, Issue 1 (IJIEPR 2020)
Abstract
This paper deals with a multi- objective linear fractional programming problem involving probabilistic parameters in the right- hand side of the constraints. These probabilistic parameters are randomly distributed with known means and variances through the use of Uniform and Exponential Distributions. After converting the probabilistic problem into an equivalent deterministic problem, a fuzzy programming approach is applied by defining a membership function. A linear membership function is being used for obtaining an optimal compromise solution. The stability set of the first kind without differentiability corresponding to the obtained optimal compromise solution is determined. A solution procedure for obtaining an optimal compromise solution and the stability set of the first kind is presented. Finally, a numerical example is given to clarify the practically and the efficiency of the study.
Hamiden Khalifa,
Volume 31, Issue 2 (IJIEPR 2020)
Abstract
This paper aims to study multi- objective assignment (NMOAS) problem with imprecise costs instead of its prices information. The NMOAS problem is considered by incorporating single valued trapezoidal neutrosophic numbers in the elements of cost matrices. After converting the NMOAS problem into the corresponding crisp multiobjective assignment (MOAS) problem based on the score function, an approach to find the most preferred neutrosophic solution is discussed. The approach is used through a weighting Tchebycheff problem which is applied by defining relative weights and ideal targets. The advantage of this approach is more flexible than the standard multi- objective assignment problem, where it allows the decision maker (DM) to choose the targets he is willing. Finally, a numerical example is given to illustrate the utility, effectiveness and applicability of the approach.
