جستجوی مقالات مرتبط با کلیدواژه "فرآیند تحلیل سلسله مراتبی" در نشریات گروه "صنایع"

Projects are used in most organizational structures including strong matrix, weak matrix, balance matrix, project-oriented, virtual, hybrid, and project management oce to achieve the goals of the organization. Many organizations consider their successful projects as a competitive advantage and use a comprehensive portfolio management system to manage projects, plans, and operations to achieve their organizational goals. As project management has become more professional, the focus of organizations has shifted from management to one or more complex projects separately and to the management of an interconnected set of projects. Therefore, a formal portfolio management process is a requirement for integrated implementation and the use of a portfolio system to manage projects to achieve the goals and strategies of the organization based on the desired criteria of management, is necessary. Income sources in almost all of the project-based companies, especially in IT Industry, are highly dependent on the company's project revenue, so Project Portfolio Selection has always been one of their managers' main concerns. To maximize their business value and protability, these companies dene appropriate projects in specic time horizons. Because the projects compete for resources, the interdependence between an organization's projects and their potential and actual impact on the portfolio selection has become particularly important to managers. Applying Analytical Hierarchy Process (AHP) technique and the Fuzzy Inference System (FIS), this paper presents a hybrid model of Fuzzy Mathematical Programming that seeks to select projects in a portfolio by creating maximum synergies between them in the presence of uncertainty. In the proposed model, the concept of synergy is used in such a way that time constraints, costs, and interactions between them are satised, and decision-makers have the opportunity to evaluate dierent selection modes. We used the fuzzy conditional programming approach in the objective function and the Jimenez method in constraints to defuzzify the problem. In order to express the eectiveness of the proposed model, it is applied in the telecom industry as a case study.

One of the novel approaches in supply chain management is Vendor-managed inventory (VMI). The aim of this policy is to establish a long-term relationship between retailers and vendors. The prerequisite for the long-term relationship of vendors with retailers is to select retailers who can meet the most criteria from the vendors' perspective and have a considerable level of reliability. In this paper, a two-tier supply chain with multiple retailers and multiple vendors has been developed using a combination of multi-criteria decision-making methods and multi-objective programming under the VMI policy. The developed model is such that, in order to establish long-term relationships and reduce supply chain costs, each retailer can only participate with one vendor. In general, the aim of the present study is to minimize costs, increase the reliability of retailers, and select retailers who have relative prominence compared to other retailers. To this end, a            hierarchical analysis process (AHP) has been performed for each vendor, and the weights of retailers relative to the suppliers have been calculated. Then, the obtained weights were input into the three-objective model designed. The proposed model, considering a combination of qualitative and quantitative criteria in selecting retailers under VMI, can find a combination of the best      retailers by balancing between the criteria. In order to maintain the long-term relationship of the vendor with the retailers, it is better for the vendor to consider important criteria that are  necessary in selecting retailers.

Supply chains play an important and integral role in today's global economy. Supply chain operations are sensitive to various uncertainties such as disruptions in suppliers, transportation disruptions, or fluctuations in customer demand. Supply chain risk management can be defined as a management activity aimed at identifying and managing risks for the supply chain through a collaborative approach among supply chain members to reduce the vulnerability of the supply chain. The aim of this study is to identify and prioritize supply chain risks of Mobarakeh Steel Complex in Isfahan through the fuzzy analytic hierarchy process. To this end, the company's supply chain risks were identified using previous research studies and interviews with relevant experts, and the most important ones were selected through questionnaires, screening, and selection. Then, these risks were classified into different categories and fuzzy pairwise comparison tables were designed and distributed among experts for collection. Finally, the relative weights of the elements in these tables were extracted using the non-linear fuzzy preference programming method, and then the final weights of each of the company's risks were obtained using the fuzzy analytic hierarchy process.

The Analytic Hierarchy Process (AHP) is a multiple criteria decision-making method extensively used in various fields. Prioritization of decision criteria or alternatives from pairwise comparison matrices in AHP has been studied extensively. This article proposed the “Double-Frontier DEA” approach for prioritization in AHP. This new approach uses two optimistic and pessimistic DEA models to obtain the best local priorities from a pairwise comparison matrix, regardless of whether it is fully consistent or not.

One of these methods is Data Envelopment Analysis (DEA). The combination of DEA and AHP (DEAHP) is used to obtain and aggregate weights in AHP. Studies show that DEAHP fails in obtaining and aggregating weights in AHP and sometimes produces priority vectors contrary to evidence for inconsistent pairwise comparison matrices that limits its application.

This new approach uses two optimistic and pessimistic DEA models to obtain the best local priorities from a pairwise comparison matrix, regardless of whether it is fully consistent or not. Some numerical examples, including a real application of AHP for selecting an innovation team for a university, are provided to specify the advantages of the proposed approach and its potential applications.

Originality/Value:

 The double-frontier DEA approach generates true weights for fully consistent pairwise comparison matrices and best local priorities for inconsistent pairwise comparison matrices, that are logical and fit subjective judgments of decision-makers.

The purpose of this research is to identify and prioritize international markets entry strategies in plastics industry.

The research method of the study is explorative-descriptive and its statistical population includes managers and officers working in small and medium-sized enterprises in the plastic industry, which are the members of the Bojnord Chamber of Commerce, Industries, and Mines. The sampling method of the study consists of snowballing sampling and purposive sampling, and the sample size is equal to 19 experts. Data collection instrument was questionnaire, which its validity and reliability were confirmed using content validity ratio and inconsistency ratio mechanism, respectively. To analyze data, Analytic Hierarchy Process (AHP) technique was used.

The findings indicate that international markets entry strategies in plastics industry consists of seven strategies, including export, license, management contract, contract manufacturing, turnkey operation, foreign direct investment and strategic alliances, and criteria to select these strategies include four categories of factors related to host country, factors related to product, factors related to company, and factors related to home country. Furthermore, the research findings indicate that the most important criterion to select international markets entry strategies is factors related to company and the best international markets entry strategy is export.

Originality/Value: 

The findings of this research help managers to evaluate, prioritize, and select international markets entry strategies using AHP technique in an effective and efficient manner.

Hub location problem is one of the most popular issues in communications and, truck transportation, air transportation, and in particular, in marine transport in recent years. The main focus of this article is on selecting and ranking the ports that suitable to be concidered as a hub for container ports. A shipping carrier not only calculates transport distances and operation costs, but also evaluates some qualitative conditions for existing hub locations and then selects an optimal container transshipment hub location in the region. Many qualitative and quantitative criteria involved in the selection of the most appropriate port as a hub. In this paper, two Multiple Criteria Decision Making (MCDM) models are applied to evaluate and select hub port in the shipping industry. Finally, performance of each presented MCDM technique have been studied in ports of south of Iran including: Abbas port, Imam, Bushehr, Khorramshahr, Chabahar and Assaluyeh and results of techniques are evaluated.

Hospitals are one of the most important centers of medical service. At the time of the occurrence of natural and abnormal disasters, the demand for these centers may increase and some of these hospitals will be damaged and lose their functionality. On the other hand, in order to protect the lives of the injured, the distance and time of their transfer to hospitals is of particular importance. The proposed problem addressed simultaneously the crisis and normal conditions and tried to determine the location of hospitals in such a way that with limited resources in hand and the normal capacity and extra that can be used in times of crisis, the minimum distances Have Taking into account the decisions of the hardening of existing hospitals and the location of new hospitals simultaneously, post-abandonment distances are reduced compared to when the location is taken regardless of disability and rehabilitation, and this can be an effective step in crisis management. The capacity of hospitals in normal conditions and in the event of a crisis is limited and considering this in the model gives more realistic results. In this research, the problem of locating new hospitals and hardening a number of existing hospitals with limited available budget has been discussed. First, the potential locations to build a hospital are specified. Then, using the proposed mathematical model, the optimal locations for the construction of new hospitals were determined, as well as decisions regarding the hardening of a number of existing hospitals. In order to solve the model due to its bi-objective function, the Epsilon-constraint Method (II) are used. To evaluate the validity of the model, a case study was carried out based on demographic and geographical information of Yazd city. Regarding the possibility of applying the model to large-scale applications and operating issues as well as NP-hardness of the model, an innovative multi-objective two-phase algorithm is proposed and evaluated based on some numerical examples.

With the advent of growing knowledge of the economy and the rapid growth of technology, intellectual property has become the focus of attention of corporate investment managers and researchers. Patent are considered to be the most important intellectual asset, and one of the reasons for this is the extensive research that has been done on the various dimensions of these rights. The patent provides the possessor with the possibility to use the technology exclusively for a limited period (often twenty years). Since many industrial and service companies need to acquire new technologies by the purchase of patent rights to maintain their competitive advantage and sustained business growth, the issue of patent assessment has become a serious challenge in the field of technology. In this research, a model for evaluating and ranking patents based on multi-criteria programming methods is presented and then the resulting model is implemented in a cell phone company. The company is required to choose a technology from four technologies: (1) a dual display, (2) missing phone tracking, (3) wireless communications security, and (4) remote banking to develop its products. The implementation of the model is based on four main criteria: (1) the essence of technology, (2) the cost of technology, (3) the product market, and (4) the technology market in the company led to the choice of wireless security technology. Also the accuracy of the result obtained from the implementation of the research model has been confirmed by the method of ELECTRE.

Sustainability approach to ensure that human use of natural cycles and resources does not lead to a decrease in quality of life due to the loss of future economic opportunities or harmful effects on social conditions, human health and the environment, emphasizing the design and operation of humans and systems. In order to maintain the sustainability of the supply chain, all supply chain members, including suppliers, manufacturers, distributors, retailers and managers, should take the sustainability principles into account. In this regard, performance appraisal and supplier selection, as one of the main components of the supply chain, plays an important role in system Sustainability. The determination of performance indicators that lead to the sustainability of suppliers are categorized into economic, social and environmental indicators. These indices have a special interest in the relationship of humans to each other and the relationship between human and the environment. The purpose of this research is to provide a gray decision making method for choosing suppliers based on the sustainability approach at SABA PVC Company. In this study, Multi-Criteria Decision Making method in gray environment has been used to select suppliers and GAHP has been used to calculate the weight and ranking of suppliers. The statistical population of this study includes 15 persons those who are involved in the selection of SABA PVC’s suppliers. In this research, the effective indicators of the selection of suppliers in SABA PVC Company are identified in the form of 3 dimensions of sustainability and 15 sub-indicators, and finally the economic dimension is known as the most important dimension of sustainability effects on the choice of suppliers. Then, the comparison and prioritization of the 6 suppliers is done and Hampar Company gets the highest priority among the six suppliers.

In recent decades, as a result of the global economic growth and the development of investment, extensive researches have been carried out in the field of ranking companies, Data Envelopment analysis (DEA) and Analytical Hierarchy Process (AHP ) are the most important methods in this field, However, perhaps the most notable method is DEA/AHP which is, in fact, the combination of the mentioned ones. This method utilizes the strengths of DEA and AHP to rank the decision-making units (DMUs) in a company.
The aim of this study is to provide a rating of cement companies operating in the stock using improved methods DEA / AHP is. The results of the research show that in 1391, Isfahan, Bojnoord and Qaen cement companies took the first to third places, but in 1392 these places belonged to Abyek, Isfahan and Cazroon companies. Therefore, it can be concluded that while using the improved integrated DEA and AHP method, not only the companies with higher efficiency are placed in higher ranks, but also, the inefficient companies are ranked effectively

Nowadays, the need to technology evaluation is increasing with development of technology in different areas and also the necessity of using modern technologies. In a general sense, technology evaluation is referred to a process during which the effects from introduction, development, change and modification for a technology are investigated in a firm by a systematic method. The weaknesses and strengths in the intended technology is specified by investigating the level of technological capabilities, and the required context for decision making is created with regard to the development of technological capabilities. This paper aims to investigate and analyze the levels of technological capabilities in SAIPA group. This research evaluates the levels of technological capability in 8 factors by a developed model and specifies the situation of the company and presents the existing gap for codifying the projects of technological modification. This is a descriptive-survey research and the data are gathered using AHP questionnaire. Hierarchy analysis is used to rank the effective factors on the capabilities. The results show that the mean technological capability of SAIPA group in the 8 factors is equal to 54.12. Also, the factor of competition state in industry obtained the highest rank among the factors in the ranking of the effective factors on technological capabilities.

Hub location problem is one of the most popular issues in communications and, truck transportation, air transportation, and in particular, in marine transport in recent years. The main focus of this article is on selecting and ranking the ports that suitable to be concidered as a hub for container ports. A shipping carrier not only calculates transport distances and operation costs, but also evaluates some qualitative conditions for existing hub locations and then selects an optimal container transshipment hub location in the region. Many qualitative and quantitative criteria involved in the selection of the most appropriate port as a hub. In this paper, two Multiple Criteria Decision Making (MCDM) models are applied to evaluate and select hub port in the shipping industry. Finally, performance of each presented MCDM technique have been studied in ports of south of Iran including: Abbas port, Imam, Bushehr, Khorramshahr, Chabahar and Assaluyeh and results of techniques are evaluated.

Supplier selection is one of the most critical activities of purchasing management in a supply chain, because of the key role of supplier's performance on cost, quality, delivery, and service in achieving the objectives of a supply chain. Selecting the right suppliers signi- cantly reduces the purchasing cost and improves corporate competitiveness, which is why many experts believe that the supplier selection is the most important activity of a purchasing department. Supplier selection is a multiple-criteria decision-making (MCDM) problem that is aected by several con icting factors. Consequently, a purchasing manager must analyze the tradeo  among several criteria. MCDM techniques support the decision makers (DMS) in evaluating a set of alternatives. In a real situation, for supplier selection problems, the weights of criteria are dierent and depend on purchasing strategies in a supply chain. Many multicriteria decision making approaches have been proposed for supplier selection, such as Analytic Hierarchy Process (AHP), Analytic Network Process (ANP), Case-based Reasoning (CBR), Data Envelopment Analysis (DEA), fuzzy set theory, Genetic Algorithm (GA), mathematical programming, Simple Multi-Attribute Rating Technique (SMART), and their hybrids. Supplier selection is a multi-criteria decision making problem, which includes both qualitative and quantitative factors. In order to select the best suppliers, it is necessary to make a trade-o between these tangible and intangible factors, some of which may con ict. When business volume discounts exist, this problem becomes more complicated as, in these circumstances, buyer should decide about two problems: which suppliers are the best and how much should be purchased from each selected supplier. In this article, an integrated approach of Analytical Hi- erarchy Process (AHP), improved by rough sets theory and multi-objective mixed integer programming, is proposed to simultaneously determine the number of suppliers to employ and the order quantity allocated to these suppliers. A solution methodology is presented to solve the multi-objective model and the model is illustrated using a numerical example.

Different methods are provided to deal with imprecise judgments of decision makers for the analytical hierarchy process. Most previous methods, which allow consideration of imprecise judgments as fuzzy numbers, provide the local and global weights of elements as fuzzy numbers too. Local and global fuzzy numbers need additional aggregation, computation and ranking procedures. The global weights may overlap each other and make the ranking of alternatives difficult. As a result, since there are different methods of fuzzy computation and fuzzy ranking, in some problems, we cannot have a unique ranking of fuzzy numbers. In order to overcome this deficiency, one method for solving fuzzy analytical hierarchy process problems and obtaining the crisp priority vector is called extent analysis. As mentioned, the main challenges of solving such problems are the fuzzy computations and ranking of fuzzy numbers, because different computation and ranking of fuzzy numbers may result in the different ranking of alternatives. Since the extent analysis method derives the crisp priority vector from fuzzy comparison matrices, it eliminates the need for additional computation and ranking of fuzzy numbers. This method is used in much research, but, in this paper, it is indicated that the priority vector of this method is not appropriate. To overcome this defect, in this paper, a new meta-heuristic based algorithm is proposed to derive the crisp priority vector from fuzzy comparison matrices. Furthermore, in order to illustrate the proposed method of this paper, it is compared with four methods available in the literature. The computational results indicate that the proposed method is appropriate for deriving the crisp priority vector from fuzzy comparison matrices.

organizations to survive and produce new productions in their surrounded environment need new technology. One of the ways to acquisition technology is transfer technology from other organization or countries. One of the most important problems which industries in developing countries are wrestling with is non-effectiveness of transferred technology. The reason for this, is the failure to complete the phases of transfer of technology or lack of improvement in these phases. The technology transfer process has six interactive phases: the selection and acquisition, adaptation, assimilation, utilization, development and diffusion. In this study, field research and studies in the field of technology transfer process is investigated and influential factors in the technology transfer process are identified. With t student model, a significant relationship between these components are reviewed and confirmed. Then through collecting expert opinions, the success of the technology transfer process is evaluated and importance of the phases are specified by extending the classical analytic hierarchy process (AHP) method and They are compared with a success rate, And by IPA, both the importance and performance aspects were evaluated so by determining priorities for improvement and resource allocation, the technology transfer process hasbeen improved. Although this work can be viewed as a case study in Samam co.

The decision to buy, sell, design and construct residential apartments is a complex process due to a combination of multiplequalitative and quantitative factors. It thus requires a great deal of costs and time for decision makers in this market. Identifying these factors and determining the priority of them are importance for selectingan apartment. The aim of current research is to identify the affecting factorsof the desirability of a residential apartment by utilizing the knowledge and experience of experts in the housing market and then determine the priority ofeach factor through AHP method. In this case, certain experts in Mashhad city were chosen in order to specify the influential factors from the customers view point and rank them through paired comparison. In the last step, qualitative and quantitative factors are combined and the assessment model for determining the value ofresidential apartment is presented.

In today’s business competitive world, decision makers of companies try to employ standard, efficient, theoretical and operational proven methods as a competitive advantage for making their critical strategic business decisions in order to survive in their industry. In this paper, a hybrid model based on Fuzzy Analytic Hierarchy Process (FAHP) and Artificial Neural Network (ANN) is presented. This model can be used as a Decision Support System (DSS) to capture and represent the decision makers’ preferences, without their direct or interference, in order to represent them the ability to select the best product among candidates. The priority of products is determined by the factors elicited from interviews and surveys. Firstly, the weight of each factor is determined by the means of FAHP technic. Then, the priority of products will be determined by weighing each of them with respect to the factors. But, the output of FAHP is just a possible answer. The topology of the neural network model is developed to train the model and give the decision makers the best possible answer. In fact, neural network is used to learn the relation among criteria and alternatives and rank the alternatives. A method based on AHP is developed and used as the MCDM method, and Multi level perceptron is used as our selected kind of artificial neural network. A case study is discussed and developed through the paper. The comparison of the real investment data of the studying case and the results of the model proves the effectiveness of the proposed model.