Samir Abass - Academia.edu (original) (raw)

Papers by Samir Abass

In many power sys tem prob lems, the use of op ti mi za tion tech niques has proved in ductive to... more In many power sys tem prob lems, the use of op ti mi za tion tech niques has proved in ductive to re duc ing the costs and losses of the sys tem. A fuzzy multi-ob jec tive de ci sion is used for solv ing power sys tem prob lems. One of the most im por tant is sues in the field of power sys tem en gi neer ing is the gen er a tion ex pan sion plan ning prob lem. In this paper, we use the con cepts of mem ber ship func tions to de fine a fuzzy de ci sion model for gen er at ing an op ti mal so lu tion for this prob lem. So lu tions ob tained by the fuzzy de cision the ory are al ways ef fi cient and con sti tute the best com pro mise.

Maintenance activity is regarded as the most important key factor for the safety, reliability and... more Maintenance activity is regarded as the most important key factor for the safety, reliability and economy of a nuclear power plant. Preventive maintenance refers to set of planned activities which include nondestructive testing and periodic inspection as well as maintenance. In this paper, we address the problem of nuclear power plant preventive maintenance scheduling with uncertainty. The uncertainty will be represente d by fuzzy parameters. The problem is how to determine the period for which generating units of an electric system should be taken off line for planned preventive maintenance over specific time horizon. Preventive maintenance activity of a nuclear power plant is an important issue as it designed to extend the plant life . It is more required to review the maintenance not only from the view point of safety and reliability but also economy. Preventive maintenance program exists to ensure that nuclear safety significant equipment will function when it is supposed to. Al...

European Journal of Engineering Research and Science, 2020

In this paper, the generalized machine maintenance problem is formulated as linear programming mo... more In this paper, the generalized machine maintenance problem is formulated as linear programming model. The objective is to maximize the percentage production hours available per maintenance cycle of each machine. Data in many real life engineering and economic problems suffers from inexactness. There are different approaches to deal with uncertain optimization problems. In this paper two different approaches of uncertainty, Fuzzy programming and rough interval programming approaches will be introduced. We deal the concerned problem with uncertain data in coefficients of the constraints for the two approaches. A numerical example is introduced to clarify the two proposed approaches. A comparison study between the obtained results of the two proposed approaches and the results of interval approach for Samir A. and Marwa Sh [3] will be introduced.

International Journal of Management Science and Engineering Management, 2012

Abstract Data in many real life engineering and economic problems suffer from inexactness. In the... more Abstract Data in many real life engineering and economic problems suffer from inexactness. In the real world there are many forms of uncertainty that affect the utility function. Uncertainty always exists in practical engineering problems. To deal with uncertain optimization problems, fuzzy, stochastic and interval numbers approaches are commonly used to describe the imprecise characteristics. Herein, we consider the estimation of the scaling constants of the additive utility function under a fuzzy environment. The investigated procedure uses the Kuhn-Tucker necessary optimality conditions. An illustrative numerical example is given to clarify the developed procedure.

International Journal of Management Science and Engineering Management, 2011

Page 1. ISSN 1750-9653, England, UK International Journal of Management Science and Engineering M... more Page 1. ISSN 1750-9653, England, UK International Journal of Management Science and Engineering Management, 6(5): 323-327, 2011 http://www.ijmsem.org/ Integer programming model for Generation Expansion Planning problem under fuzzy environment ...

International Journal of Management Science and Engineering Management, 2010

... Samir A. Abass ... Bilevel programming problem (Ankhili and Mansouri, 2009 [1]; Arora and Rit... more ... Samir A. Abass ... Bilevel programming problem (Ankhili and Mansouri, 2009 [1]; Arora and Ritu, 2009 [2]; Colson et al., 2005 [8]; Dempe, 2003 [10]; Herminia and Carmen, 2004 [16]; Her-minia et al., 2008 [17]) has been proposed for dealing with decision processes involving two ...

Journal of Advances in Mathematics and Computer Science, 2018

In this study, the multiple knapsack problems (MKP) with uncertainty model is introduced. The unc... more In this study, the multiple knapsack problems (MKP) with uncertainty model is introduced. The uncertainty represents the capacities of the knapsack. A possibility degree of interval number is used to convert the uncertain capacities to deterministic capacities. Some basic stability notions in parametric multiple knapsack are defined. These notions are the set of feasible parameters, the solvability set and the stability set of the first kind. A numerical example (case study) is introduced to present the suggested approach.

This paper presents a solution algorithm for solving the single machine early/tardy problem havin... more This paper presents a solution algorithm for solving the single machine early/tardy problem having fuzzy parameters in the constraints. There are several cost structures: job-independent, job-dependent and symmetric, and job-dependent and asymmetric. The last problem is shown to be NP-hard and it will be studied here. Some basic stability notions are defined and characterized for the problem of concern. These notions are the set of feasible parameters, the solvability set and the stability set of the first kind. A parametric study is carried out for the problem of concern. Finally, an illustrative numerical example is given to clarify. the theory and the solution algorithm.

This paper presents a solution algorithm for solving the job-shop scheduling problem involving fu... more This paper presents a solution algorithm for solving the job-shop scheduling problem involving fuzzy parameters in the constraints. It is considered that the processing times are those fuzzy parameters and the maximum completion time is required to be minimized. The concept of α - level set together with the definition of the fuzzy number and its membership function are introduced. An illustrative numerical example is given to clarify the theory and the solution algorithm

$Research paper thumbnail of A parametric study for the linear fractional programming problem under uncertainty$

International Journal of Management Science and Engineering Management, 2015

Abstract In this paper, a linear fractional programming problem with interval coefficients in bot... more Abstract In this paper, a linear fractional programming problem with interval coefficients in both objective function and constraints is solved. The uncertain objective function is transformed into two deterministic objective functions. The two objective functions are converted into a single objective problem through the linear combination method. Through a modified possibility degree, the uncertain inequality and equality constraints are transformed into deterministic inequality constraints. The existing results are concerning the qualitative and quantitative analysis of basic notions in parametric linear fractional programming problem. These notions are the set of feasible parameters, the solvability set and the stability set of the first kind. A numerical example is investigated to demonstrate the effectiveness of the present approach.

American Journal of Operational Research, 2012

Data in many real life engineering and economical problems suffer fro m inexactness. In the real ... more Data in many real life engineering and economical problems suffer fro m inexactness. In the real world there are many forms of uncertainty that affect production processes. Uncertainty always exists in practical engineering problems. in order to deal with the uncertain optimization problems, fuzzy and stochastic approaches are co mmonly used to describe the imprecise characteristics. Herein we assume some intervals in which the data can simultaneously and independently perturb. In this study production planning related data of Al-Araby firm fo r electric sets in Egypt was collected. A production planning model based on linear programming (LP) was formulated. This formulat ion based on the outcomes of collected data. The data includes the amount of required and availab le resources, the demand, the cost of production, the cost of unmet demand, the cost of inventory holding and the revenue. in this work, the objective is to maximize the revenues net of the production, inventory and lost sales costs. The general LP model was solved by using software named W in QSB.

Open Journal of Applied Sciences, 2012

The traditional production planning model based upon the famous linear programming formulation ha... more The traditional production planning model based upon the famous linear programming formulation has been well known in the literature. The consideration of uncertainty in manufacturing systems supposes a great advance. Models for production planning which do not recognize the uncertainty can be expected to generate inferior planning decisions as compared to models that explicitly account the uncertainty. This paper deals with production planning problem with fuzzy parameters in both of the objective function and constraints. We have a planning problem to maximize revenues net of the production inventory and lost sales cost. The existing results concerning the qualitative and quantitative analysis of basic notions in parametric production planning problem with fuzzy parameters. These notions are the set of feasible parameters, the solvability set and the stability set of the first kind.

Nuclear Technology and Radiation Protection, 2007

In many power system problems, the use of optimization techniques has proved inductive to reducin... more In many power system problems, the use of optimization techniques has proved inductive to reducing the costs and losses of the system. A fuzzy multi-objective decision is used for solving power system problems. One of the most important issues in the field of power system engineering is the generation expansion planning problem. In this paper, we use the concepts of membership functions to define a fuzzy decision model for generating an optimal solution for this problem. Solutions obtained by the fuzzy decision theory are always efficient and constitute the best compromise. .

... 165-176 A PARAMETRIC STUDY ON TRANSPORTATION PROBLEM UNDER FUZZY ENVIRONMENT Omar IVI. ... me... more ... 165-176 A PARAMETRIC STUDY ON TRANSPORTATION PROBLEM UNDER FUZZY ENVIRONMENT Omar IVI. ... method for solving GTP was presented by Balas [1] and an operator theory of pa/ametric programming for GTP was presented by Balachandran and Thompson [2-...

Computational Management Science, 2005

This paper presents a fuzzy bilevel programming approach to solve the flow shop scheduling proble... more This paper presents a fuzzy bilevel programming approach to solve the flow shop scheduling problem. The problem considered here differs from the standard form in that operators are assigned to the machines and imposing a hierarchy of two decision makers with fuzzy processing times. The shop owner considered higher level and assigns the jobs to the machines in order to minimize the flow time while the customer is the lower level and decides on a job schedule in order to minimize the makespan. In this paper, we use the concepts of tolerance membership function at each level to define a fuzzy decision model for generating optimal (satisfactory) solution for bilevel flow shop scheduling problem. A solution algorithm for solving this problem is given.