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Showing 7 results for Mohammadi

Mohammad Ali Farajian , Shahriar Mohammadi ,
Volume 21, Issue 4 (IJIEPR 2010)
Abstract

  The unprecedented growth of competition in the banking technology has raised the importance of retaining current customers and acquires new customers so that is important analyzing Customer behavior, which is base on bank databases. Analyzing bank databases for analyzing customer behavior is difficult since bank databases are multi-dimensional, comprised of monthly account records and daily transaction records. Few works have focused on analyzing of bank databases from the viewpoint of customer behavioral analyze. This study presents a new two-stage frame-work of customer behavior analysis that integrated a K-means algorithm and Apriori association rule inducer. The K-means algorithm was used to identify groups of customers based on recency, frequency, monetary behavioral scoring predicators it also divides customers into three major profitable groups of customers. Apriori association rule inducer was used to characterize the groups of customers by creating customer profiles. Identifying customers by a customer behavior analysis model is helpful characteristics of customer and facilitates marketing strategy development .


M. Mohammadi, R. Tavakkoli-Moghaddam, A. Ghodratnama , H. Rostami ,
Volume 22, Issue 3 (IJIEPR 2011)
Abstract

 

  Hub covering location problem, Network design,

  Single machine scheduling, Genetic algorithm,

  Shuffled frog leaping algorithm

 

Hub location problems (HLP) are synthetic optimization problems that appears in telecommunication and transportation networks where nodes send and receive commodities (i.e., data transmissions, passengers transportation, express packages, postal deliveries, etc.) through special facilities or transshipment points called hubs. In this paper, we consider a central mine and a number of hubs (e.g., factories) connected to a number of nodes (e.g., shops or customers) in a network. First, the hub network is designed, then, a raw materials transportation from a central mine to the hubs (i.e., factories) is scheduled. In this case, we consider only one transportation system regarded as single machine scheduling. Furthermore, we use this hub network to solve the scheduling model. In this paper, we consider the capacitated single allocation hub covering location problem (CSAHCLP) and then present the mixed-integer programming (MIP) model. Due to the computational complexity of the resulted models, we also propose two improved meta-heuristic algorithms, namely a genetic algorithm and a shuffled frog leaping algorithm in order to find a near-optimal solution of the given problem. The performance of the solutions found by the foregoing proposed algorithms is compared with exact solutions of the mathematical programming model .


Ali Mohaghar, Mojtaba Kashef, Ehsan Kashef KhanMohammadi,
Volume 25, Issue 2 (IIJEPR 2014)
Abstract

Considering the major change occurred in business cells from plant to “chain” and the critical need to choose the best partners to form the supply chain for competing in today’s business setting, one of the vital decisions made at the early steps of constructing a business is supplier selection. Given the fact that the early decisions are inherently strategic and therefore hard and costly to change, it’s been a point of consideration for industries to select the right supplier. It’s clear that different criteria must be investigated and interfered in deciding on the best partner(s) among the alternatives. Thereupon the problem might be regarded as a multiple criteria decision making (MCDM) problem. There are a variety of techniques to solve a MCDM problem. In this paper we propose a novel technique by combination of decision making trial and evaluation laboratory and graph theory and matrix approach techniques. Eventually, the results are compared to SAW technique and discussed to come to a conclusion.
Amir-Mohammad GolMohammadi, Mahboobeh Honarvar, Hasan Hosseini-Nasab, Reza Tavakkoli-Moghaddam,
Volume 29, Issue 2 (IJIEPR 2018)
Abstract

The fundamental function of a cellular manufacturing system (CMS) is based on definition and recognition of a type of similarity among parts that should be produced in a planning period. Cell formation (CF) and cell layout design are two important steps in implementation of the CMS. This paper represents a new nonlinear mathematical programming model for dynamic cell formation that employs the rectilinear distance notion to determine the layout in the continuous space. In the proposed model, machines are considered unreliable with a stochastic time between failures. The objective function calculates the costs of inter and intra-cell movements of parts and the cost due to the existence of exceptional elements (EEs), cell reconfigurations and machine breakdowns. Due to the problem complexity, the presented mathematical model is categorized in NP-hardness; thus, a genetic algorithm (GA) is used for solving this problem. Several crossover and mutation strategies are adjusted for GA and parameters are calibrated based on Taguchi experimental design method. The great efficiency of the proposed GA is then demonstrated via comparing with particle swarm optimization (PSO) and the optimum solution via GAMS considering several small/medium and large-sized problems. 


Mahdi Karbasian, Maryam Mohammadi, Mohammad Mortazavi,
Volume 29, Issue 2 (IJIEPR 2018)
Abstract

Reliability allocation has an essential connection to design for reliability and is an important activity in the product design and development process. In determining the reliability of subsystems or components on the basis of goal reliability, attention must be paid to failure effect, failure information, and improvement opportunities based upon real potentials for reliability improvement. In the light of the fact that ignoring dependent failures inflicts irreversible damage on systems, and that redundant systems are vulnerable to Common Cause Failure (CCF) as well as independent failure, attention must be paid not only to components’ independent failure information, but also to CCF information in conducting reliability allocation for such systems. To consider improved failure rate alone cannot ensure the achievement of the goal reliability in question, because if the CCF occurrence exceeds a certain limit, the system’s reliability will certainly fail to match the goal reliability. This paper is an attempt to develop a method for reliability allocation of series-parallel systems by considering CCF, in such a way that potentials and priorities of reliability improvement are taken into consideration. The proposed method consists of four stages: 1) adding a series component to the redundant system in order to investigate CCF, 2) conducting reliability allocation for series components and the redundant system, 3) conducting reliability allocation for redundant system components, and 4) analyzing the failure rate of system components. The proposed method is run for water pumping systems and the results are evaluated. In this method, in addition to the improved failure rate of system components, the improved rate of CCF is computed, too. This proves instrumental and crucial for system designers in feasibility studies and conceptual design.
 

Arezoo Jahani, Parastoo Mohammadi, Hamid Mashreghi,
Volume 29, Issue 2 (IJIEPR 2018)
Abstract

Innovation & Prosperity Fund (IPfund) in Iran as a governmental organization aims to develop new technology-based firms (NTBF) by its available resources through financing these firms. The innovative projects which refer to IPfund for financing are in a stage which can receive both fixed rate facilities and partnership in the projects, i.e. profit loss sharing (PLS). Since this fund must protect its initial and real value of its capital against inflation rate, therefore, this study aims to examine the suitable financing methods with considering risk. For this purpose we study on risk assessment models to see how to use risk adjusted net present value for knowledge based projects. On this basis, the NPV of a project has been analyzed by taking into account the risk variables (sales revenue and the cost of fixed investment) and using Monte Carlo simulation. The results indicate that in most cases for a project, the risk adjusted NPV in partnership scenario is more than the other scenario. In addition to, partnership in projects which demand for industrial production facilities is preferable for the IPfund than projects calling for working capital.
Zahra Touni, Ahmad Makui, Emran Mohammadi,
Volume 30, Issue 1 (IJIEPR 2019)
Abstract

Financial decision-making is the principal part of any decisions hence great efforts are done to improve the methods to assess and analyze the stock in financial markets as a part of the financial decision. This paper addresses the stock selection by discovering investor's utility function .Investors in the Stock Exchange consider diverse criteria to buy shares and bonds. Due to the criteria development in stock selection, understanding the investor's behavior by a consultant is a prominent issue. Recognizing an exclusive utility function according to the characteristics of the investors facilitates acquiring each share's value for the decision maker (DM) when it is required. In this study, UTASTAR method is used to estimate the marginal value function, using 3 appropriate criteria (risk, return, liquidity) and finally fit out the total utility function. It provides the opportunity to make a rational decision fit to investor's mentality and allowing their ranking, prioritization, selection or classification. The ranking of the options is as compatible as possible to the original one. The method is applied to an example from Iran Stock Exchange.



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