570 research outputs found

    A Novel Project Risk Assessment Method Development via AHP-TOPSIS Hybrid Algorithm

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    In project planning, risk assessment method plays vital role. Poorly assessed project risks cause degeneration at project cost, project completion time, and project output quality and project scope. Each project activity risk influence these project success factors. Implementation performance of a project activity triggers or smooth of its successor’s activity risks. Because of this; employing robust and detailed risk assessment methods is important to reach those project goals. In project risk assessment literature, when it is investigated, it is noticed that risk assessment and evaluation methods are only developed at whole project level. Actually, they are not comprehensive enough to evaluate the project risks at activity level. Besides that traditional risk assessment methods such as risk matrix does not able analyze project risk quantitatively. With this motivation, main aim of this study is developing a multi-criteria based decision method which prioritizing project risks at activity level. AHP and TOPSIS method are combined to developed novel method. In this hybrid method, Constructing AHP model is to prioritize work packages with respect to relative importance of project time, project output quality and project cost. Broken down structure of these work packages are used as input for weighted criteria for TOPSIS method. In second layer of this decision method, TOPSIS model is used for prioritizing predetermined activity risks according weighted project work packages success criteria. In the application of this method, a case study approach is followed. In this sense, “Global Furniture Ltd.” which is established in Istanbul, Turkey is chosen as a case to apply newly developed model. Results showed that application of AHP-Stochastic TOPSIS Hybrid Algorithm provides a platform that project risks could be analyzed as quantitative and also at project activity level

    Using Pythagorean Fuzzy Sets (PFS) in Multiple Criteria Group Decision Making (MCGDM) Methods for Engineering Materials Selection Applications

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    The process of materials’ selection is very critical during the initial stages of designing manufactured products. Inefficient decision-making outcomes in the material selection process could result in poor quality of products and unnecessary costs. In the last century, numerous materials have been developed for manufacturing mechanical components in different industries. Many of these new materials are similar in their properties and performances, thus creating great challenges for designers and engineers to make accurate selections. Our main objective in this work is to assist decision makers (DMs) within the manufacturing field to evaluate materials alternatives and to select the best alternative for specific manufacturing purposes. In this research, new hybrid fuzzy Multiple Criteria Group Decision Making (MCGDM) methods are proposed for the material selection problem. The proposed methods tackle some challenges that are associated with the material selection decision making process, such as aggregating decision makers’ (DMs) decisions appropriately and modeling uncertainty. In the proposed hybrid models, a novel aggregation approach is developed to convert DMs crisp decisions to Pythagorean fuzzy sets (PFS). This approach gives more flexibility to DMs to express their opinions than the traditional fuzzy and intuitionistic sets (IFS). Then, the proposed aggregation approach is integrated with a ranking method to solve the Pythagorean Fuzzy Multi Criteria Decision Making (PFMCGDM) problem and rank the material alternatives. The ranking methods used in the hybrid models are the Pythagorean Fuzzy TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) and Pythagorean Fuzzy COPRAS (COmplex PRoportional Assessment). TOPSIS and COPRAS are selected based on their effectiveness and practicality in dealing with the nature of material selection problems. In the aggregation approach, the Sugeno Fuzzy measure and the Shapley value are used to fairly distribute the DMs weight in the Pythagorean Fuzzy numbers. Additionally, new functions to calculate uncertainty from DMs recommendations are developed using the Takagai-Sugeno approach. The literature reveals some work on these methods, but to our knowledge, there are no published works that integrate the proposed aggregation approach with the selected MCDM ranking methods under the Pythagorean Fuzzy environment for the use in materials selection problems. Furthermore, the proposed methods might be applied, due to its novelty, to any MCDM problem in other areas. A practical validation of the proposed hybrid PFMCGDM methods is investigated through conducting a case study of material selection for high pressure turbine blades in jet engines. The main objectives of the case study were: 1) to investigate the new developed aggregation approach in converting real DMs crisp decisions into Pythagorean fuzzy numbers; 2) to test the applicability of both the hybrid PFMCGDM TOPSIS and the hybrid PFMCGDM COPRAS methods in the field of material selection. In this case study, a group of five DMs, faculty members and graduate students, from the Materials Science and Engineering Department at the University of Wisconsin-Milwaukee, were selected to participate as DMs. Their evaluations fulfilled the first objective of the case study. A computer application for material selection was developed to assist designers and engineers in real life problems. A comparative analysis was performed to compare the results of both hybrid MCGDM methods. A sensitivity analysis was conducted to show the robustness and reliability of the outcomes obtained from both methods. It is concluded that using the proposed hybrid PFMCGDM TOPSIS method is more effective and practical in the material selection process than the proposed hybrid PFMCGDM COPRAS method. Additionally, recommendations for further research are suggested

    An integrated method for airline company supplier selection based on the entropy and vikor methods: a real case study

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    All certified airlines require to implement a safety and quality management system. Therefore, the quality of all services and products with critical operational domains have been challenging issues in the aviation industry. In this regard, supplier selection plays an important role to acquire competitive benefits. Flight operations is critical scope in an airline and their outputs have a direct impact on flight safety consequences. Therefore, the quality of supplier’s product and services play the main role in their flight operations process. In this research, a new decision-making framework is developed to evaluate the performance of the suppliers based on the Entropy and VIKOR approaches. At the outset, the main criteria and sub-criteria are identified based on the literature and expert\u27s viewpoint and then their weights are calculated using the Entropy method. Afterward, the potential suppliers are ranked using the VIKOR method. The airline supplier’s assessment through expert judgment and integrated criteria are the new approaches that are developed in this paper. The obtained results show that economic, quality and safety, and reputation respectively are the main criteria to select suppliers

    Deciding a multicriteria decision-making (Mcdm) method to prioritize maintenance work orders of hydroelectric power plants

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    The current global competitive scenario and the increase in complexity and automation of equipment and systems demand better results from maintenance management in organizations. As maintenance resources are limited, prioritizing maintenance activities is essential to allocate them properly and to meet maintenance management objectives. In the face of these challenges, multicriteria decision-making (MCDM) methods are commonly used in organizations to support decision-making. Nevertheless, selecting a suitable MCDM method for maintenance planning can be complicated given the diversity of methods and their strengths and weaknesses. In this context, this paper proposes a novel knowledge-based method for deciding a multicriteria decision-making (MCDM) method to prioritize maintenance work orders of hydroelectric plants. As the main novel contribution, it translates the intrinsic characteristics of the main MCDM methods into questions related to maintenance planning to guide the recommendation of a suitable MCDM method for organizations through a decision tree diagram. This approach was applied to a maintenance case study of a hydroelectric power plant in order to demonstrate its use and contribute to its understanding. These findings contribute to maintenance management in selecting an MCDM method aligned with the context of its maintenance planning for the prioritization of maintenance work orders

    Urban Planning Using a Geospatial Approach: A Case Study of Libya

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    Large scale developmental projects firstly require the selection of one or more cities to be developed. In Libya, the selection process is done by selected organizations, which is highly influenced by human judgement that can be inconsiderate of socioeconomic and environmental factors. In this study, we propose an automated selection process, which takes into consideration only the important factors for city (cities) selection. Specifically, a geospatial decision-making tool, free of human bias, is proposed based on the fuzzy overlay (FO) and technique for order performance by similarity to ideal solution (TOPSIS) techniques for development projects in Libya. In this work, a dataset of 17 evaluation criteria (GIS factors) across five urban conditioning factors were prepared. The dataset served as input to the FO model to calculate weights (importance) for each criterion. A support vector machine (SVM) classifier was then trained to refine weights from the FO model. TOPSIS was then applied on the refined results to rank the cities for development. Experimental results indicate promising overall accuracy and kappa statistics. Our findings also show that highest and lowest success rates are 0.94 and 0.79, respectively, while highest and lowest prediction rates are 0.884 and 0.673, respectively

    The state of the art development of AHP (1979-2017): A literature review with a social network analysis

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    Although many papers describe the evolution of the analytic hierarchy process (AHP), most adopt a subjective approach. This paper examines the pattern of development of the AHP research field using social network analysis and scientometrics, and identifies its intellectual structure. The objectives are: (i) to trace the pattern of development of AHP research; (ii) to identify the patterns of collaboration among authors; (iii) to identify the most important papers underpinning the development of AHP; and (iv) to discover recent areas of interest. We analyse two types of networks: social networks, that is, co-authorship networks, and cognitive mapping or the network of disciplines affected by AHP. Our analyses are based on 8441 papers published between 1979 and 2017, retrieved from the ISI Web of Science database. To provide a longitudinal perspective on the pattern of evolution of AHP, we analyse these two types of networks during the three periods 1979?1990, 1991?2001 and 2002?2017. We provide some basic statistics on AHP journals and researchers, review the main topics and applications of integrated AHPs and provide direction for future research by highlighting some open questions

    The state of the art development of AHP (1979-2017): a literature review with a social network analysis

    Get PDF
    Although many papers describe the evolution of the analytic hierarchy process (AHP), most adopt a subjective approach. This paper examines the pattern of development of the AHP research field using social network analysis and scientometrics, and identifies its intellectual structure. The objectives are: (i) to trace the pattern of development of AHP research; (ii) to identify the patterns of collaboration among authors; (iii) to identify the most important papers underpinning the development of AHP; and (iv) to discover recent areas of interest. We analyse two types of networks: social networks, that is, co-authorship networks, and cognitive mapping or the network of disciplines affected by AHP. Our analyses are based on 8441 papers published between 1979 and 2017, retrieved from the ISI Web of Science database. To provide a longitudinal perspective on the pattern of evolution of AHP, we analyse these two types of networks during the three periods 1979–1990, 1991–2001 and 2002–2017. We provide some basic statistics on AHP journals and researchers, review the main topics and applications of integrated AHPs and provide direction for future research by highlighting some open questions

    Identification and Prioritization of Critical Risk Factors of Commercial and Recreational Complex Building Projects: A Delphi Study Using the TOPSIS Method

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    Construction development of Commercial and Recreational Complex Building Projects (CRCBPs) is one of the community needs of many developing countries. Since the implementation of these projects is usually very costly, identifying and evaluating their Critical Risk Factors (CRFs) are of significant importance. Therefore, the current study aims to identify and prioritize CRFs of CRCBPs in the Iranian context. A descriptive-survey method was used in this research; the statistical population, selected based on the purposive sampling method, includes 30 construction experts with hands-on experience in CRCBPs. A questionnaire related to the risk identification stage was developed based on a detailed study of the research literature and also using the Delphi survey method; 82 various risks were finally identified. In order to confirm the opinions of experts in identifying the potential risks, Kendall’s coefficient of concordance was used. In the first stage of data analysis, qualitative evaluation was performed by calculating the severity of risk effect and determining the cumulative risk index, based on which 25 CRFs of CRCBPs were identified for more accurate evaluation. At this stage, the identified CRFs were evaluated based on multi-criteria decision-making techniques and using the TOPSIS technique. Results show that the ten CRFs of CRCBPs are external threats from international relations, exchange rate changes, bank interest rate fluctuations, traffic licenses, access to skilled labor, changes in regional regulations, the condition of adjacent buildings, fluctuations and changes in inflation, failure to select a suitable and qualified consultant, and employer’s previous experiences and records. Obviously, the current study’s results and findings can be considered by CRCBPs in both the private and public sectors for proper effective risk identification, evaluation, and mitigatio

    Fuzzy Approach in Ranking of Banks according to Financial Performances

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    Evaluating bank performance on a yearly basis and making comparison among banks in certain time intervals provide an insight into general financial state of banks and their relative position with respect to the environment (creditors, investors, and stakeholders). The aim of this study is to propose a new fuzzy multicriteria model to evaluate banks respecting relative importance of financial performances and their values. The relative importance of each pair of financial performance groups is assessed linguistic expressions which are modeled by triangular fuzzy numbers. Fuzzy Analytic Hierarchical Process (FAHP) is applied to determine relative weights of the financial performances. In order to rank the treated banks, new model based on Fuzzy Technique for Order Performance by Similarity to Ideal Solution (FTOPSIS) is deployed. The proposed model is illustrated by an example giving real life data from 12 banks having 80% share of the Serbian market. In order to verify the proposed FTOPSIS different measures of separation are used. The presented solution enables the ranking of banks, gives an insight of bank's state to stakeholders, and provides base for successful improvement in a field of strategy quality in bank business

    ODABIR MANAGERA KONTROLE KVALITETE NA OSNOVI AHP-COPRAS-G METODA: SLUČAJ U IRANU

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    Due to the increasing competition of globalization and fast technological improvements and world markets, demands of companies to have professional human resources are increasing too. It is an important problem of an organization to select the most appropriate personnel among the candidates. Quality control manager is important personnel in organizations and it’s so important to select the best candidate for this work. In this paper we proposed a personnel selection system based on Analytic Hierarchy Process (AHP) and Complex proportional assessment of alternatives with grey relations (COPRAS-G) method. At first seven criteria is identified including: knowledge of product and raw material properties, Experience and educational background, Administrative orientation, Behavioral flexibility, Risk evaluation ability, Payment and Team work and after that AHP applied for calculating weight of each criteria and finally using COPRAS- G method for selecting the best candidate for this job. This study can be used as a pattern for personnel selection and future researches.S obzirom na rastuću konkurentnost u globalizaciji te brzim tehnološkim napredovanjem na svjetskom tržištu, zahtjevi kompanija za profesionalnim kadrom se također povećavaju. Vrlo je važno za organizaciju biti u mogućnosti odabrati najbolji i najprimjereniji kadar među ponuđenim kandidatima. Manager kontrole kvalitete je važan kadar u bilo kojoj organizaciji tako da je iznimno važno za taj posao odabrati najbolje kandidate. U ovom radu predlažemo sustav odabira kadra zasnovan na analitičkom hijerarhijskom procesu (AHP) i kompleksnoj proporcionalnoj evaluaciji alternativa sa sivim odnosima (COPRAS-G). Isprva je identificirano sedam kriterija uključujući: znanje o proizvodu i svojstvima sirovine, iskustvo i obrazovanje, snalaženje s administracijom, fleksibilnost u ponašanju, sposobnost procjene rizika, plaćanja i timski rad te je zatim primijenjen AHP za izračunavanje težine svakog kriterija te je naposljetku korištena COPRAS-G metoda za odabir najboljih kandidata. Ova studija se može koristiti kao predložak za odabir kandidata i buduća istraživanja
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