Showing 23 results for Shah
K. Shahanaghi, V.r. Ghezavati,
Volume 19, Issue 4 (IJIE 2008)
Abstract
In this paper, we present the stochastic version of Maximal Covering Location Problem which optimizes both location and allocation decisions, concurrently. It’s assumed that traveling time between customers and distribution centers (DCs) is uncertain and described by normal distribution function and if this time is less than coverage time, the customer can be allocated to DC. In classical models, traveling time between customers and facilities is assumed to be in a deterministic way and a customer is assumed to be covered completely if located within the critical coverage of the facility and not covered at all outside of the critical coverage. Indeed, solutions obtained are so sensitive to the determined traveling time. Therefore, we consider covering or not covering for customers in a probabilistic way and not certain which yields more flexibility and practicability for results and model. Considering this assumption, we maximize the total expected demand which is covered. To solve such a stochastic nonlinear model efficiently, simulation and genetic algorithm are integrated to produce a hybrid intelligent algorithm. Finally, some numerical examples are presented to illustrate the effectiveness of the proposed algorithm.
Kamran Shahanaghi, Hamid Babaei , Arash Bakhsha,
Volume 20, Issue 1 (IJIEPR 2009)
Abstract
In this paper we focus on a continuously deteriorating two units series equipment which its failure can not be measured by cost criterion. For these types of systems avoiding failure during the actual operation of the system is extremely important. In this paper we determine inspection periods and maintenance policy in such a way that failure probability is limited to a pre-specified value and then optimum policy and inspection period are obtained to minimize long-run cost per time unit. The inspection periods and maintenance policy are found in two phases. Failure probability is limited to a pre-specified value In the first phase, and in the second phase optimum maintenance thresholds and inspection periods are obtained in such a way that minimize long-run expected.
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 .
P.k Shahabadkar, J.s Sujit Kumar , K.s Prashant ,
Volume 22, Issue 4 (IJIEPR 2011)
Abstract
There has been a recent development and explosion of interest among academicians across a wide range of disciplines in the use of virtual Class room. Utilization of the virtual class room as a laboratory experimentation for teaching and learning has increased significantly in recent years as development tools for web based applications have become easier to use and computers have become more capable and less expensive. But, does the virtual class-room improve students learning? Herein we describe the results of two experiments conducted on sections of a Manufacturing and Operation Management course [MIME - 3240] at one of the Colleges of Technology in the Sultanate of Oman during fall semester. Two experiments were designed to determine if student learning of Manufacturing and Operation Management course was significantly affected by two treatments: 1) Virtual class room environment for the students of section S2 and 2) Real Class-room environment for students of section S1. The actual final scores of students of section S1 and S2 were compared in order to determine the effectiveness of virtual class room on student learning for the Manufacturing and Operation Management course.
In this study Web-based virtual Class room (WVC) is developed to communicate, to share and to disseminate knowledge from the teacher to student. Further, in this study web based tools are also used to create, store, and manage contents of class room instructions and course material .
Pramod Shahabadkar,
Volume 23, Issue 3 (IJIEPR 2012)
Abstract
Abstract
Purpose-The purpose of this paper is to review a sample of the literature relating to Interpretive Structural Modelling (ISM) and its deployment for modelling purposes in the area of supply chain management (SCM).
Design/methodology/approach- The literature is examined from the three perspectives. First, concept of ISM and examines ISM as modelling technique. Second, use of ISM by the various researchers in their research for modelling. Third, use of ISM for modelling in the area of supply chain management.
Findings- ISM is a systematic application of some elementary graph theory in such a way that theoretical, conceptual and computational advantage are exploited to explain the complex pattern of conceptual relations among the variables. From the literature review, we can conclude that many researchers have used ISM for modelling the variables of: reverse logistics, vendor managed inventory, IT enabled supply chain management etc.
Research limitation/implications-The scope of this literature review is by design limited to ISM and it does not cover in investigating other modelling techniques. Literature review investigates sample of important and influential work in the area of application of ISM in the research.
Originality/Value-This study reviews a sample of recent and classic literature in this field and in doing so this paper provides some comprehensive base and clear guidance to researchers in developing, defining and presenting their research agenda for applying ISM methodology in a systematic and convincing manner.
Key words: Interpretive Structural Modelling, SCI, SMEs, SCM
Ali Shahandeh Nookabadi, Mohammad Reza Yadoolahpour, Soheila Kavosh,
Volume 24, Issue 1 (IJIEPR 2013)
Abstract
Network location models comprise one of the main categories of location models. These models have various applications in regional and urban planning as well as in transportation, distribution, and energy management. In a network location problem, nodes represent demand points and candidate locations to locate the facilities. If the links network is unchangeably determined, the problem will be an FLP (Facility Location Problem). However, if links can be added to the network at a reasonable cost, the problem will then be a combination of facility location and NDP (Network Design Problem) hence, called FLNDP (Facility Location Network Design Problem), a more general variant of FLP. In previous studies of this problem, capacity of facilities was considered to be a constraint while capacity of links was not considered at all. The proposed MIP model considers capacity of facilities and links as decision variables. This approach increases the utilization of facilities and links, and prevents the construction of links and location of facilities with low utilization. Furthermore, facility location cost (link construction cost) in the proposed model is supposed to be a function of the associated facility (link) capacity. Computational experiments as well as sensitivity analyses performed indicate the efficiency of the model.
Shervin Asadzadeh , Abdollah Aghaie, Hamid Shahriari ,
Volume 24, Issue 2 (IJIEPR 2013)
Abstract
Monitoring the reliability of products in both the manufacturing and service processes is of main concern in today’s competitive market. To this end, statistical process control has been widely used to control the reliability-related quality variables. The so-far surveillance schemes have addressed processes with independent quality characteristics. In multistage processes, however, the cascade property must be effectively justified which entails establishing the relationship among quality variables with the purpose of optimal process monitoring. In some cases, measuring the values corresponding to specific covariates is not possible without great financial costs. Subsequently, the unmeasured covariates impose unobserved heterogeneity which decreases the detection power of a control scheme. The complicated picture arises when the presence of a censoring mechanism leads to inaccurate recording of the process response values. Hence, frailty and Cox proportional hazards models are employed and two regression-adjusted monitoring procedures are constructed to effectively account for both the observed and unobserved influential covariates in line with a censoring issue. The simulation-based study reveals that the proposed scheme based on the cumulative sum control chart outperforms its competing procedure with smaller out-of-control average run length values.
Navid Khademi, Afshin Shariat Mohaymany, Jalil Shahi, Mojtaba Rajabi,
Volume 24, Issue 3 (IJIEPR 2013)
Abstract
Most of the researches in the domain of fuzzy number comparisons serve the fuzzy number ordering purpose. For making a comparison between two fuzzy numbers, beyond the determination of their order, it is needed to derive the magnitude of their order. In line with this idea, the concept of inequality is no longer crisp however it becomes fuzzy in the sense of representing partial belonging or degree of membership. In this paper we propose a method for capturing the membership degree of fuzzy inequalities through discretizing the μ-axis into equidistant intervals. It calculates m in the fuzzy inequalities ≤ m and ≥m among two normal fuzzy numbers. In this method, the two μ-axis based discretized fuzzy numbers are compared point by point and at each point the degree of preferences is identified. To show its validity, this method is examined against the essential properties of fuzzy number ordering methods in [Wang, X. and E.E. Kerre, Reasonable properties for the ordering of fuzzy quantities (I). Fuzzy Sets and Systems, 2001. 118(3): p. 375-385.] The result provides promising outcomes that may be useful in the domain fuzzy multi criteria or multi-attribute decision making analysis and also fuzzy mathematical programming with fuzzy inequality constraints.
Iraj Mahdavi, Mohammad Mahdi Paydar, Golnaz Shahabnia,
Volume 26, Issue 3 (IJIEPR 2015)
Abstract
Disasters can cause many casualties and considerable destruction mainly because of ineffective preventive measures, incomplete preparedness, and weak relief logistics systems. After catastrophic events happen, quick and effective response is of great importance, so as to having an efficient logistic plan for distributing needed relief commodities efficiently and fairly among affected people. In this paper, we propose a fuzzy multi-objective, multi-modal, multi-commodity logistic model in emergency response to disaster occurrence, to assign limited resources equitably to the infected regions in a way to minimize transfer costs of commodities as well as distribution centers activation costs, and maximizing satisfied demand. In the proposed model, we have determined the optimal place of distribution centers among candidate points to receive people donations as well as sending and receiving different kinds of relief commodities. The amount of voluntary donations is not known precisely and is estimated with uncertainty, so we have used fuzzy parameters for them. The number of victims immediately after disaster is vague and is estimated indecisively though we have considered it as a fuzzy demand. A case study has been displayed to test the properties of the optimization problem that shows efficiency of this formulation in experiment.
Nita Shah, Chetan Vaghela,
Volume 28, Issue 2 (IJIEPR 2017)
Abstract
Abstract
In this research, an integrated inventory model for non-instantaneous deteriorating items is analyzed when demand is sensitive to changes in price. The price used in this research is a time-dependent function of the initial selling price and the discount rate. To control the deterioration rate of items at the storage facility, investment in preservation technology is incorporated. To provide a general framework to the model, an arbitrary holding cost rate is used. Toward the end of the paper, a numerical case is given to approve the model and the impacts of the key parameters of the model are studied by sensitivity analysis to deduce managerial insights.
Arash Khosravi, Seyed Reza Hejazi, Shahab Sadri,
Volume 28, Issue 4 (IJIEPR 2017)
Abstract
Managing income is a considerable dimension in supply chain management in current economic atmosphere. Real world situation makes it inevitable not to design or redesign supply chain. Redesign will take place as costs increase or new services for customers’ new demands should be provided. Pricing is an important fragment of Supply chain due to two reasons: first, represents revenue based each product and second, based on supply-demand relations enables Supply chain to provide demands by making suitable changes in facilities and their capacities. In this study, Benders decomposition approach used to solve multi-product, multi-echelon and multi-period supply chain network redesign including price-sensitive customers.
Naser Safaei, Shahnaz Piroozfar, Seyedehfatemeh Golrizgashti,
Volume 30, Issue 3 (IJIEPR 2019)
Abstract
Supply chain management is a set of used methods for the efficient integration of suppliers, manufacturers, warehouses, and sellers to response customer requirements to reduce system costs and to distribute products at the right place and right time. This study aims to identify and rank the supply chain damages using the analytic network process as a practical case in a fast moving consumer goods (FMCG-food industry) company. Firstly the supply chain damages are explored according to literature review. In the next step the most important damages are identified into four cluster of supply include
supply, production, distribution and support. Then, the weight of each identified damages based on its effects on other damages are calculated by using the analytic network process approach. According to results, the most important supply chain damages are logistics, distribution, competition and changing market tastes. The obtained results can provide practical discussion and solutions for similar companies to improve your market share and customer satisfaction.
Parham Azimi, Shahed Sholekar,
Volume 32, Issue 1 (IJIEPR 2021)
Abstract
According to the real projects’ data, activity durations are affected by numerous parameters. In this research, we have developed a multi-resource multi objective multi-mode resource constrained scheduling problem with stochastic durations where the mean and the standard deviation of activity durations are related to the mode in which each activity is performed. The objective functions of model were to minimize the net present value and makespan of the project. A simulation-based optimization approach was used to handle the problem with several stochastic events. This feature helped us to find several solutions quickly while there was no need to take simplification assumptions. To test the efficiency of the proposed algorithm, several test problems were taken from the PSPLIB directory and solved. The results show the efficiency of the proposed algorithm both in quality of the solutions and the speed.
Pramod Shahabadkar, Prashant Shahabadkar, Ashok Vanageri, S.s.hebbal ,
Volume 32, Issue 2 (IJIEPR 2021)
Abstract
Increasing competition due to globalization, product diversity and technological breakthroughs stimulate independent firms to collaborate in a supply chain that allows gaining the mutual benefits. This requires a collective coordination framework and migration path to synchronize and to integrate the information systems and also organizational activities of the supply chain partners. However, existing research in supply chain integration has paid little attention in identifying and developing a migration path to know the present level of supply chain among the supply chain partners. Hence, the objective of this paper is to develop a framework for supply chain integration. In the proposed research, the informational, organizational and information technology integration is operationalized for the development of Supply Chain Integration framework for manufacturing industries. Further, this paper includes a comprehensive understanding of supply chain integration in general and specifically organizational, informational and IT integration. The developed framework for supply chain integration is validated by a pilot study and it helps the organizations to know the present level and provides a migration path to move to the next level of supply chain integration. This paper will add onto the contribution of authors who have ventured study in the area of supply chain integration.
Seyed Hamid Zahiri, Najme Ghanbari, Hadi Shahraki,
Volume 33, Issue 2 (IJIEPR 2022)
Abstract
In current study, a particle swarm clustering method is suggested for clustering triangular fuzzy data. This clustering method can find fuzzy cluster centers in the proposed method, where fuzzy cluster centers contain more points from the corresponding cluster, the higher clustering accuracy. Also, triangular fuzzy numbers are utilized to demonstrate uncertain data. To compare triangular fuzzy numbers, a similarity criterion based on the intersection region of the fuzzy numbers is used. The performance of the suggested clustering method has been experimented on both benchmark and artificial datasets. These datasets are used in the fuzzy form. The experiential results represent that the suggested clustering method with fuzzy cluster centers can cluster triangular fuzzy datasets like other standard uncertain data clustering methods. Experimental results demonstrate that, in almost all datasets, the proposed clustering method provides better results in accuracy when compared to Uncertain K-Means and Uncertain K-medoids algorithms.
Mehrnaz Piroozbakht, Sedigh Raissi, Meysam Rafei, Shahrooz Bamdad,
Volume 33, Issue 2 (IJIEPR 2022)
Abstract
In a system, prediction of remaining useful lifetime (RUL) of servicing before reaching to a specified breakdown threshold is a very important practical issue, and research in this field is still regarded as an appreciated research gap. Operational environment of an equipment is not constant and changes regarding to stresses and shocks. These random environmental factors accelerate system deterioration by affecting on the level or rate of degradation path. The present study focuses on providing a practical operational guideline to estimate the RUL of a system with general degradation path after receiving a shock which only affects on the degradation level. Due to exact estimation of the shock arrival times and measuring the magnitudes of future shocks to investigate shock effects on RUL is almost impossible in the real world and laborious in practice, in this research a new procedure based on total defect size monitored in the constant inspection periods and Accelerated Factor (AF) is proposed to analyze RUL of the system. A Micro-Electro-Mechanical system (MEMS) is used as an example and the results show the applicability of the proposed approach.
Shahla Zandi, Reza Samizadeh, Maryam Esmaeili,
Volume 33, Issue 4 (IJIEPR 2022)
Abstract
A coalition loyalty program (CLP) is a business strategy employed by for-profit companies to increase or retain their customers. One of the operational challenges of these programs is how to choose the mechanism of coordination between business partners. This paper examines the role of revenue sharing contracts in the loyalty points supply chain of a CLP with stochastic advertising-dependent demand where the program operator (called the host) sells loyalty points to the partners of the program. The purpose of the study is to examine the effect of this coordination mechanism on the decisions and profits of the members of the chain using the Stackelberg game method and determine whether the presence of revenue sharing contracts benefits the chain members when the advertising is done by the host and when the advertising cost is shared between the host and its partners. The results show that when the host gives bonus points to end customers (advertising), revenue sharing contracts become a powerful incentive for the profitability of the host and its partners. The findings provide new insights into the management of CLPs, which can benefit business decision-makers.
Shahla Zandi, Reza Samizadeh, Maryam Esmaeili,
Volume 34, Issue 3 (IJIEPR 2023)
Abstract
A coalition loyalty program (CLP) is a business strategy adopted by companies to increase and retain their customers. An operational challenge in this regard is to determine the coordination mechanism with business partners. This study investigated the role of revenue-sharing contracts (RSCs) considering customer satisfaction in coalition loyalty reward supply chain planning. A two-stage stochastic programming approach was considered for the solution considering the demand uncertainty. We aimed to investigate the impact of RSCs on the decision-making and profitability of the host firm of this supply chain taking into account the maximization of the profit coming from the CLP compared to the more common wholesale price contract (WPC). After the model was solved, computational experiments were performed to evaluate and compare the effects of RSCs and WPCs on the performance of the loyalty program (LP). The results revealed that RSC is an effective incentive to increase the host’s profit and reduce its cost. These findings add new insights to the management literature, which can be used by business decision makers.
Seyed Erfan Mohammadi, Emran Mohammadi, Ahmad Makui, Kamran Shahanaghi,
Volume 34, Issue 4 (IJIEPR 2023)
Abstract
Since 1952, when the mean-variance model of Markowitz introduced as a basic framework for modern portfolio theory, some researchers have been trying to add new dimensions to this model. However, most of them have neglected the nature of decision making in such situations and have focused only on adding non-fundamental and thematic dimensions such as considering social responsibilities and green industries. Due to the nature of stock market, the decisions made in this sector are influenced by two different parameters: (1) analyzing past trends and (2) predicting future developments. The former is derived objectively based on historical data that is available to everyone while the latter is achieved subjectively based on inside-information that is only available to the investor. Naturally, due to differences in the origin of their creation the bridge between these two types of analysis in order to optimize the portfolio will be a phenomenon called "ambiguity". Hence, in this paper, we revisited Markowitz's model and proposed a modification that allow incorporating not only return and risk but also incorporate ambiguity into the investment decision making process. Finally, in order to demonstrate how the proposed model can be applied in practice, it is implemented in Tehran Stock Exchange (TSE) and the experimental results are examined. From the experimental results, we can extract that the proposed model is more comprehensive than Markowitz's model and has greater ability to cover the conditions of the stock market.
Mansour Abedian, Amirhossein Karimpour, Morteza Pourgharibshahi, Atefeh Amindoust,
Volume 35, Issue 2 (IJIEPR 2024)
Abstract
The area coverage of machines on the production line to address the scheduling and routing problem of autonomous guided vehicles (AGV) is an innovative way to improve productivity in manufacturing enterprises. This paper proposed a new model for the optimal area coverage of machines in the production line by applying a single AGV to minimize both the transfer costs and the number of breakpoints of AGV. One of the unique advantages of the area coverage employed in the present study is that it minimizes transfer costs and breakpoints, and makes it possible to provide service for several machines simultaneously since the underlying assumption was finding a path to ensure that every point in a given workspace is covered at least once. Since rail AGV is used in this study, AGV can only pass horizontal and vertical distances in the production line. The reversal of the AGV path in vertical and horizontal distances implies failure and breakpoint in the present paper. The simulation results confirm the feasibility of the proposed method.