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Showing 34 results for Rahim

J. Fathikalajahi, M. Baniadam , R. Rahimpour ,
Volume 19, Issue 3 (International Journal of Engineering 2008)

 An equation-oriented approach was developed for steady state flowsheeting of a commercial methanol plant. The loop consists of fixed bed reactor, flash separator, preheater, coolers, and compressor. For steady sate flowsheeting of the plant mathematical model of reactor and other units are needed. Reactor used in loop is a Lurgi type and its configuration is rather complex. Previously reactor and flash separator are modeled as two important units of plant. The model is based on mass and energy balances in each equipment and utilizing some auxiliary equations such as rate of reaction and thermodynamics model for activity coefficients of liquid. In order to validate the mathematical model for the synthesis loop, some simulation data were performed using operating conditions and characteristics of the commercial plant. The good agreement between the steady state simulation results and the plant data shows the validity of the model.
Gh. Rahimi , Ar. Davoodinik ,
Volume 19, Issue 7 (IJES 2008)

The intention of this study is the analysis of thermal behavior of functionally graded beam (FGB). The distribution of material properties is imitated exponential function. For thermal loading the steady state of heat conduction with exponentially and hyperbolic variations through the thickness of FGB, is considered. With comparing of thermal behavior of both isotropic beam and FGB, it is appea red that the quality of temperature distribution plays very important part in thermal resultant distribution of stresses and strains for FGB. So that, for detecting the particular thermal behavior of FGB, the function of heat distribution must be same as function of material properties distribution. In addition, In the case of exponential distribution of heat with no mechanical loads, in spite of the fact that the bending is accrued, the neutral surface does not come into existence.

Jafar Mahmudi, Soroosh Nalchigar , Seyed Babak Ebrahimi,
Volume 20, Issue 1 (IJIEPR 2009)

Selection of an appropriate set of Information System (IS) projects is a critical business activity which is very helpful to all organizations. In this paper, after describing real IS project selection problem of Iran Ministry of Commerce (MOC), we introduce two Data Envelopment Analysis (DEA) models. Then, we show applicability of introduced models for identifying most efficient IS project from 8 competing projects. Then, in order to provide further insight, results of two introduced models are compared. It is notable that using basic DEA models -CCR and BCC- decision maker is not able to find most efficient Decision Making Unit (DMU) since these models identify some of DMUs as efficient which their efficiency scores equal to 1. As an advantage, the applied models can identify most efficient IS (in constant and variable return to scale situations) by solving only one linear programming (LP). So these models are computationally efficient. It is while using the basic DEA models requires decision maker to solve a LP for each IS.
M. Ebrahimi, R. Farnoosh,
Volume 20, Issue 4 (IJIEPR 2010)

This paper is intended to provide a numerical algorithm based on random sampling for solving the linear Volterra integral equations of the second kind. This method is a Monte Carlo (MC) method based on the simulation of a continuous Markov chain. To illustrate the usefulness of this technique we apply it to a test problem. Numerical results are performed in order to show the efficiency and accuracy of the present method.
Mahdi Karbasian, Zoubi Ibrahim,
Volume 21, Issue 2 (IJIEPR 2010)

  This expository article shows how the maximum likelihood estimation method and the Newton-Raphson algorithm can be used to estimate the parameters of the power-law Poisson process model used to analyze data from repairable systems .

Rasoul Haji, Mohammadmohsen Moarefdoost, Seyed Babak Ebrahimi,
Volume 21, Issue 4 (IJIEPR 2010)

  This paper aims to evaluate inventory cost of a Two-echelon serial supply chain system under vendor managed inventory program with stochastic demand, and examine the effect of environmental factors on the cost of overall system. For this purpose, we consider a two-echelon serial supply chain with a manufacturer and a retailer. Under Vendor managed inventory program, the decision on inventory levels are made by manufacturer centrally. In this paper, we assume that the manufacturer monitors inventory levels at the retailer location and replenishes retailer's stock under (r, n, q) policy moreover, the manufacturer follows make-to-order strategy in order to respond retailer's orders. In the other word, when the inventory position at the retailer reaches reorder point, r, the manufacturer initiates production of Q=nq units with finite production rate, p. The manufacturer replenishes the retailer's stock with replenishment frequency n, and the complete batch of q units to the retailer during the production time. We develop a renewal reward model for the case of Poisson demand, and drive the mathematical formula of the long run average total inventory cost of system under VMI. Then, by using Monte Carlo simulation, we examine the effect of environmental factors on the cost of overall system under VMI .

, ,
Volume 23, Issue 2 (IJIEPR 2012)

The Network Design Problem (NDP) is one of the important problems in combinatorial optimization. Among the network design problems, the Multicommodity Capacitated Network Design (MCND) problem has numerous applications in transportation, logistics, telecommunication, and production systems. The MCND problems with splittable flow variables are NP-hard, which means they require exponential time to be solved in optimality. With binary flow variables or unsplittable MCND, the complexity of the problem is increased significantly. With growing complexity and scale of real world capacitated network design applications, metaheuristics must be developed to solve these problems. This paper presents a simulated annealing approach with innovative representation and neighborhood structure for unsplittable MCND problem. The parameters of the proposed algorithms are tuned using Design of Experiments (DOE) method and the Design-Expert statistical software. The performance of the proposed algorithm is evaluated by solving instances with different dimensions from OR-Library. The results of the proposed algorithm are compared with the solutions of CPLEX solver.  The results show that the proposed SA can find near optimal solution in much less time than exact algorithm.
Nasim Nahavandi, Ebrahim Asadi Gangraj,
Volume 25, Issue 1 (IJIEPR 2014)

Flexible flow shop scheduling problem (FFS) with unrelated parallel machines contains sequencing in flow shop where, at any stage, there exists one or more processors. The objective consists of minimizing the maximum completion time. Because of NP-completeness of FFS problem, it is necessary to use heuristics method to address problems of moderate to large scale problem. Therefore, for assessment the quality of this heuristic, this paper develop a global lower bound on FFS makespan problems with unrelated parallel machines.
Laya Olfat, Maghsoud Amiri, Jjahanyar Bamdad Soofi, Mostafa Ebrahimpour Azbari,
Volume 25, Issue 2 (IIJEPR 2014)

Having a comprehensive evaluation model with reliable data is useful to improve performance of supply chain. In this paper, according to the nature of supply chain, a model is presented that able to evaluate the performance of the supply chain by a network data envelopment analysis model and by using the financial, intellectual capital (knowledge base), collaboration and responsiveness factors of the supply chain. At the first step, indicators were determined and explained by explanatory Factor Analysis. Then, Network Data Envelopment Analysis (NDEA) model was used. This paper is the result of research related to supply chain of pharmaceutical companies in Tehran Stock Exchange and 115 experts and senior executives have been questioned as sample. The results showed that responsiveness latent variable had the highest correlation with supply chain performance and collaborative, financial and intellectual capital (knowledge base) latent variables were respectively after that. Four of the twenty eight supply chains which were studied obtained 1 as the highest performance rate and the lowest observed performance was 0.43.
Dr. Yahia Zare Mehrjerdi, Amir Ebrahimi Zade, Dr. Hassan Hosseininasab,
Volume 26, Issue 3 (IJIEPR 2015)

Abstract One of the basic assumptions in hub covering problems is considering the covering radius as an exogenous parameter which cannot be controlled by the decision maker. Practically and in many real world cases with a negligible increase in costs, to increase the covering radii, it is possible to save the costs of establishing additional hub nodes. Change in problem parameters during the planning horizon is one of the key factors causing the results of theoretical models to be impractical in real world situations. To dissolve this problem in this paper a mathematical model for dynamic single allocation hub covering problem is proposed in which the covering radius of hub nodes is one of the decision variables. Also Due to NP-Hardness of the problem and huge computational time required to solve the problem optimally an effective genetic algorithm with dynamic operators is proposed afterwards. Computational results show the satisfying performance of the proposed genetic algorithm in achieving satisfactory results in a reasonable time. Keywords: hub location problem, dynamic hub covering problem, flexible covering radius, dynamic genetic algorithm.


Hooman Abdollahi, Seyed Babak Ebrahimi, Ali Farmani,
Volume 27, Issue 3 (IJIEPR 2016)

Presently, emerging economies are acquiring singular positions all over the world. The complexities of nowadays economy have caused international companies and investors to be of a tendency towards emerging markets for more profitability and growth. This study aims to find the relationships between firm's profitability and growth in Iranian manufacturing industry consisting of Tehran Stock Market listed manufacturing firms covering 2005-2014. In order to understand the direction of causality between firm growth and profitability, we use system-GMM (Generalized Method of Moments) to estimate growth and profit regressions. The results obtained indicate that there is positively bilateral relationship between profitability and growth in the case of Iranian manufacturing firms. Also, we find the positive impact of current profit (growth) on current growth (profit) is stronger than the impact of the prior year.  

Seyed Babak Ebrahimi, Seyed Morteza Emadi,
Volume 27, Issue 4 (IJIEPR 2016)

Empirical studies show that there is stronger dependency between large losses than large profit in financial market, which undermine the performance of using symmetric distribution for modeling these asymmetric. That is why the assuming normal joint distribution of returns is not suitable because of considering the linier dependence, and can be lead to inappropriate estimate of VaR. Copula theory is basic tool for multivariate modeling, which is defined by using marginal and dependencies between variables joint distribution function. In addition, Copulas are able to explain and describe of complex multiple dependencies structures such as non-linear dependence. Therefore, in this study, by combining symmetric and asymmetric GARCH model for modeling the marginal distribution of variables and Copula functions for modeling financial data and also use of DCC model to determine the dynamic correlation structure between assets, try to estimate the Value at Risk of investment portfolio consists of five active index In Tehran Stock Exchange. The results demonstrate excellence of GJR-GARCH(1,1) with the distribution of t-student for marginal distribution. t-Copula model, estimates the Value at Risk model less than the Gaussian Copula in all cases.

Ali Salmasnia, Ebrahim Ghasemi, Hadi Mokhtari,
Volume 27, Issue 4 (IJIEPR 2016)

This study aims to select optimal maintenance strategy for components of an electric motor of the National Iranian Oil Refining and Distribution Company. In this regard, a method based on revised multi choice goal programming and analytic hierarchy process (AHP) is presented. Since improving the equipment reliability is an important issue, reliability centered maintenance (RCM) strategies are introduced in this paper. Furthermore, on one hand, we know that maintenance cost consists of a considerable percentage of production cost; on the other hand, the risk of equipment failure is a main factor on personnel’s safety. Consequently, the cost and risk factors are selected as important criteria of maintenance strategies.

Ebrahim Asadi Gangraj,
Volume 28, Issue 1 (IJIEPR 2017)

In hybrid flow shop scheduling problem (HFS) with unrelated parallel machines, a set of n jobs are processed on k machines. A mixed integer linear programming (MILP) model for the HFS scheduling problems with unrelated parallel machines has been proposed to minimize the maximum completion time (makespan). Since the problem is shown to be NP-complete, it is necessary to use heuristic methods to tackle the moderate to large scale problems. This article presents a new bottleneck-based heuristic to solve the problem. To improve the performance of the heuristic method, a local search approach is embedded in the structure of the heuristic method. To evaluate the performance of the proposed heuristic method, a new lower bound is developed based on Kurz and Askin [1] lower bound. For evaluation purposes, two series of test problems, small and large size problems, are generated under different production scenarios.  The empirical results show that average difference between lower bound and optimal solution as well as lower bound and heuristic method are equal to 2.56% and 5.23%, respectively. For more investigation, the proposed heuristic method is compared by other well-known heuristics in the literature. The results verify the efficiency of the proposed heuristic method in term of number of best solution.

Ebrahim Teimoury, Farshad Saeedi, Ahmad Makui,
Volume 28, Issue 1 (IJIEPR 2017)

Recently, urbanization has been expanded rapidly in the world and a number of metropolitan areas have been appeared with a population of more than 10 million people. Because of dense population in metropolitan and consequently increasing the delivery of goods and services, there has been a lot of problems including traffic congestion, air pollution, accidents and high energy consumption. This made some complexities in distribution of urban goods; Therefore, it is essential to provide creative solutions to overcome these complexities. City logistics models can be effective in solving these complexities.

In this paper, concepts and definitions related to city logistics are explained to provide a mathematical model in order to design city logistics distribution network aim at minimizing response times. This objective is effective for goods and emergency services, especially in times of crisis and also for goods that are delivered as soon as possible. This is a three-level network and has been used in modeling of queuing theory. To validate the model, a numerical example has been established and results of the model have been explained using BARON solver in Gams software. Finally, conclusions and recommendations for future research are presented.

Sina Nayeri, Ebrahim Asadi-Gangraj, Saeed Emami,
Volume 29, Issue 1 (IJIEPR 2018)

Natural disasters, such as earthquakes, tsunamis, and hurricanes cause enormous harm during each year. To reduce casualties and economic losses in the response phase, rescue units must be allocated and scheduled efficiently, such that it is a key issues in emergency response. In this paper, a multi-objective mix integer nonlinear programming model (MOMINLP) is proposed to minimize sum of weighted completion times of relief operations as first objective function and makespan as second objective with considering time-window for incidents. The rescue units also have different capability and each incident just can be allocated to a rescue unit that has the ability to do it. By assuming the incidents and rescue units as jobs and machine, respectively, the research problem can be formulated as a parallel-machine scheduling problem with unrelated machines. Multi-Choice Goal programming (MCGP) is applied to solve research problem as single objective problem. The experimental results shows the superiority of the proposed approach to allocate and schedule the rescue units in the natural disasters.

Mojtaba Hamid, Mahdi Hamid, Mohammad Mahdi Nasiri, Mahdi Ebrahimnia,
Volume 29, Issue 2 (IJIEPR 2018)

Surgical theater is one of the most expensive hospital sources that a high percentage of hospital admissions are related to it. Therefore, efficient planning and scheduling of the operating rooms (ORs) is necessary to improve the efficiency of any healthcare system. Therefore, in this paper, the weekly OR planning and scheduling problem is addressed to minimize the waiting time of elective patients, overutilization and underutilization costs of ORs and the total completion time of surgeries. We take into account the available hours of ORs and the surgeons, legal constraints and job qualification of surgeons, and priority of patients in the model. A real-life example is provided to demonstrate the effectiveness and applicability of the model and is solved using ε-constraint method in GAMS software. Then, data envelopment analysis (DEA) is employed to obtain the best solution among the Pareto solutions obtained by ε-constraint method. Finally, the best Pareto solution is compared to the schedule used in the hospitals. The results indicate the best Pareto solution outperforms the schedule offered by the OR director.
Ebrahim Mazrae Farahani, Reza Baradaran Kazemzade, Amir Albadvi, Babak Teimourpour,
Volume 29, Issue 3 (IJIEPR 2018)

Studying the social networks plays a significant role in everyone’s life. Recent studies show the importance and increasing interests in the subject by modeling and monitoring the communications between the network members as longitudinal data. Typically, the tendency for modeling the social networks with considering the dependency of an outcome variable on the covariates is growing recently. However, these studies fail in considering the possible correlation between the responses in the modeling of social networks. Our study use generalized linear mixed models (GLMMs) (also referred to as random effects models) to model the social network according to the attributes of nodes in which the nodes take a role of random effect or hidden effect in the modeling. The likelihood ratio test (LRT) statistics is implemented to detect change points in the simulated network streams. Also, in the simulation studies, we applied root mean square Error (RMSE) and standard deviation criteria for choosing an appropriate distribution for simulation data. Also, our simulation studies demonstrates an improvement in the average run length (ARL) index in comparison to the previous studies.
Hossein Sayyadi Tooranloo, Sajad Rahimi,
Volume 29, Issue 3 (IJIEPR 2018)

Health care centers as an important part of health care industry, in addition to following their major mission, that is, providing high quality health service, can gain environmental and even socioeconomic advantages through reducing environmental effects resulted from their activities. With the goal of gaining these advantages, health care centers can increase their environmental performance through adopting a systematic and proper approach in application of information systems (ISs). The Green information systems (ISs) that indicate a novice approach in application of ISs are considered as necessary tools to realize the goals of environmental sustainability. Different factors affect Green ISs adoption by health care centers. In this research, these factors were first identified through library method and review of the literature. Then, the relationships between these factors were analyzed and modeled using interpretive structural approach. According to the results, the volume of social investment, research and development along with the senior management’s insight and commitment are the most important factors affecting Green ISs adoption in the health care centers.
Gholamreza Gholampour, Abdul Rahman Bin Abdul Rahim, Faezeh Gholampour,
Volume 29, Issue 4 (IJIEPR 2018)

Nowadays, automakers have faced complexity of supply chain that have to improve procedures and processes in order to access high performance in both strategic and operational. The main purpose of this research is to evaluate model of strategic performance of supply chain (SPSC), which include information technology (IT), organizational learning (OL), and Product innovation (PRI) via qualitative research. In fact, this research follows how these factors effect on SPSC. IRANKHODRO Company (IKCO) as the biggest automaker in Middle East is our case study in order to research and evaluate mentioned model. A total number of 12 interviews were done based on a list of semi-structured open-ended questions in order to evaluate constructs and model. The development of constructs in IKCO according to respondents’ opinion was classified at three categories including high, medium and low levels. In high level, IT has been developed in IKCO more than another constructs, which consists of development of ORACLE system, SAP and KANBAN in order to cover information, procedures and processes across supply chain. While SPSC has been developed less than others.

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