Maher Ali Nawkhass

Dr. Maher Ali Nawkhass is a lecturer in the Mathematics Department at Salahaddin University in Erbil, Iraq. He holds a Ph.D. in Optimization – Applied Mathematics, focusing on solving complex mathematical problems across various fields. His research interests lie in the realm of fractional programming, where he develops innovative approaches to tackle multi-objective problems and optimize solutions.

Dr. Nawkhass is an experienced educator with a diverse teaching background, encompassing calculus, numerical analysis, and computer skills. His work has been recognized through publications in international journals like the International Journal of Nonlinear Analysis and Applications and the International Journal of Fuzzy System Applications. He is dedicated to fostering a deeper understanding of mathematics and its applications within the academic community.

Scopus Publications

Revised Harmonious Fuzzy Technique for Solving Fully Fuzzy Multi-Objective Linear Fractional Programming Problems
Maher A. Nawkhass
Salahaddin University - Erbil
The revised harmonious fuzzy technique (RHFT) is a method used to solve fuzzy optimization problems. It was capitalized as an extension of the classical linear programming technique to handle constraints and objectives that are fuzzy. The harmonious fuzzy technique HFT aims to find a solution that satisfies the uncertain restraints and optimizes the uncertain objectives while taking into account the uncertainty or fuzziness of the problem parameters. This work demonstrates how the RHFT can be utilized to dexterously solve “fully fuzzy multi-goal linear fractional programming (FFMOLFP) problems”. Initially, the FFMOLFP problem can be converted to “single goal linear fractional programming (SOLFP) problems” consuming the modified brittle linear technique. Second, the RHFT is applied to converted brittle problems into linear programming problem, which follow, “the single-goal problem” is made on so on applied the revised harmonious fuzzy for apiece level. at the end, the obtained LPP will be solved by applied the simplex algorithm. To illustrate the application of this method, two examples will be provided. Also, the numerical results are simulated by comparing between proposed method and efficient ranking function methods for fully fuzzy linear fractional programming problems FFLFPP

Using Geometric Arithmetic Mean to Solve Non-linear Fractional Programming Problems
Maher A. Nawkhass and Nejmaddin A. Sulaiman
Springer Science and Business Media LLC

Modify Symmetric Fuzzy Approach to Solve the Multi-objective Linear Fractional Programming Problem
Maher Ali Nawkhass and Nejmaddin Ali Sulaiman
IGI Global
The property of fuzzy sets is approached as an instrument for the construction and finding of the value of the multi-objective linear fractional programming problem (MOLFPP), which is one of the systems of decision problems that are covered by fuzzy dealings. The paper introduces an approach to convert and solve such a problem by modifying the symmetric fuzzy approach, suggesting an algorithm, and demonstrating how the fuzzy linear fractional programming problem (FLFPP) can be answered without raising the arithmetic potency. Also, it introduces a technique that uses an optimal mean to convert MOLFPP to a single LFPP by modifying the symmetric fuzzy approach. A numeric sample is provided to clarify the qualification of the suggested approach and compare the results with other techniques, which are solved by using a computer application to test the algorithm of the above method, indicating that the results obtained by the fuzzy environment are promising.

A new modified simplex method to solve quadratic fractional programming problem and compared it to a traditional simplex method by using pseudoaffinity of quadratic fractional functions
Nejmaddin A. Suleiman and Maher A. Nawkhass
Hikari, Ltd.
In this paper, we defined a new modified simplex method to solve quadratic fractional programming problem (QFPP) and suggested an algorithm for it. The algorithm of usual simplex method is also reported. The special case for this problem was solved by Converting objective function to pseudoaffinity of quadratic fractional functions (PQFF) to a linear programming problem to be solved by simplex method. Then the result is compared with a result, which obtained by new modified simplex method. These methods demonstrated by numerical examples. This work confirms that our techniques is valid and can be used to solve this particular type of QFPP.

Maher Ali Nawkhass

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