Membership maximization prioritization methods for fuzzy analytic hierarchy process

Determining road handling priority is considered as a complicated multicriteria decision making problem. In so doing, the Analytic Hierarchy Process (AHP) has been widely used to weight the importance. Fuzziness and vagueness however, are typical in many decision-making problems, so that fuzzy sets could be integrated with the pairwise comparison as an extension of the AHP. This study uses Fuzzy Analytic Hierarchy Process (FAHP) and TOPSIS method in determining regencial road handling priority for road links under severe circumstances in Badung regency in Bali province. Data are taken from a previous study, which had also been conducted for Badung regencial road handling priority using the AHP and SK.NO.77/KPTS/Db/1990 method. The weights of main and sub criteria are determined using FAHP and subsequently the ranking of road links is determined using TOPSIS method. The AHP method gave somewhat different result to 'SK.NO.77/KPTS/Db/1990' method. On the other hand, FAHP and TOPSIS method produce the same result to 'SK.NO.77/KPTS/Db/1990' method. This is probably best explained by the fact that they similarly considered traffic volumes as the most significant factor. FAHP and TOPSIS method however, are preferred to the AHP and SK.NO.77/KPTS/Db/1990 method in determining regencial road handling priority in Badung regency.Abstrak. Prioritas penanganan jalan merupakan salah satu tugas berat dan penting yang dihadapi oleh pengambil keputusan pada pemerintah daerah. Pada kenyataannya, penentuan penanganan jalan dapat dilihat sebagai permasalahan pengambilan keputusan yang melibatkan banyak kriteria yang bersifat kompleks. Metode proses hirarki analitik (AHP) telah banyak digunakan untuk menentukan bobot kriteria di dalam penentuan prioritas penanganan jalan. Akan tetapi karena keragu-raguan merupakan hal yang lazim terjadi di dalam pengambilan keputusan, maka teknik fuzzy dapat dikombinasikan ke dalam metode AHP. Pada studi ini penentuan prioritas penanganan jalan kabupaten untuk kondisi rusak berat di Kabupaten Badung, Bali dilakukan dengan metode Fuzzy AHP (FAHP) dan TOPSIS. Data penelitian digunakan dari studi sebelumnya di Kabupaten Badung yang menggunakan metode AHP dan SK.NO.77/KPTS/Db/1990. Metode FAHP digunakan untuk pembobotan kriteria sedangkan metode TOPSIS digunakan untuk penentuan urutan ruas jalan yang akan mendapat penanganan. Metode AHP memberikan hasil yang sedikit berbeda dengan metode SK.NO.77/KPTS/Db/1990. Sementara itu FAHP dan metode TOPSIS memberikan hasil yang sama dengan metode SK.NO.77/KPTS/Db/1990. Hal ini kemungkinan karena kedua metode tersebut menggunakan volume lalu lintas sebagai faktor yang paling berpengaruh pada penelitian ini. FAHP dan metode TOPSIS lebih disarankan untuk digunakan di dalam penentuan prioritas penanganan jalan di Kabupaten Badung.

The analytic hierarchy process (AHP) was first proposed by Saaty in 1980. Numerous approaches engaged on extending AHP under fuzzy environment, i.e. fuzzy analytic hierarchy process (FAHP), to solve fuzzy multi-criteria decision-making (FMCDM) projects. According to Chang's extent analysis method was a famous one of FAHP. In the method, priority vectors computation in matrix is hard for comparing fuzzy numbers on pair-wise, and possibility degrees calculation has drawback for some specifying fuzzy numbers. To resolve the above ties, we apply utility representative function for FAHP. Through the utility representative function, FAHP easily and quickly solves FMCDM problems.

In order to evaluate the performance of complex product, a fuzzy method based on fuzzy matter-element and Fuzzy Analytical Hierarchy Process (FAHP) is proposed. According to the quality objective and performance indicators, the system index of performance evaluation model is designed. Through FAHP and the model of fuzzy comprehensive estimation, the weights of evaluation index are determined for each performance criteria. Then, the performance of complex mechanical and electrical product can be identified by using the fuzzy matter-element theory and FAHP. Finally, A case study is presented to prove the method's feasibility and validity.

Convenience in online transactions on B2C website is an essential thing in the business processes. Comfort and ease of use in human and computer interaction are called usability. Therefore, developers and online store's owners are highly recommended to evaluate the usability of B2C e-commerce websites to find the extent of the severity of a website. Previous research states that the Extent Analysis (EA) approach to the Fuzzy Analytical Hierarchy Process (FAHP) method is one way to determine the weight of the usability criteria. However, it turns out there are other ways to derive the weight of the criteria in the FAHP method, which is a non-linear programming approach called Fuzzy Preference Programming (FPP). This study aims to compare EA and FPP approach to determine the proper ones on evaluating B2C website usability. A comparative analysis shows that these two methods have significant differences. However, the EA method produces several weights with a value of 0, which causes criteria to be ignored in the calculation. The FPP method can eliminate EA weakness. All criteria remain weighted so that the criteria value can use in the usability score calculation. Based on this result, it can be said that the FPP method is better in generating the weight of the criteria used in usability score calculation.

The applied technology university focuses on cultivating practical skill graduates. So the quality of its graduates is an important evaluation index. Because the evaluation of graduates quality is a complex and systematic project, the Fuzzy AHP (Fuzzy Analytic Hierarchy Process) was selected to evaluate the quality of graduates in W university, which combines Fuzzy mathematics theory and AHP. With analysis, the quality of W university students is general. And the school has a good background, but the execution and feedback of theoretical and practical courses need to be strengthened. According to calculation, the weights of four categories of indicators are similar, which indicates that applied-type transformation is a systematic engineering that should pay attention to the whole process. On the other hand, the weight of graduates' employment quality is the most important index, reflecting the strong adaptability of applied-technical talents to employment environment. The technology-oriented universities should strengthen the communication with enterprises and graduates.KeywordsGraduate qualityUniversity of applied technologyFuzzy AHP

Using Fuzzy AHP to manage Intellectual Capital assets: An application to the ICT service industry

The purpose of this study is to develop an effective tool for the courseware design and assessment. A case study for the energy saving education was taken as the example for assessment. The model, which combines Fuzzy Delphi Method and Fuzzy Analytic Hierarchy Process, was developed in this research to evaluate the courseware in teaching process. The candidate indexes were selected from the most important factors of the summary of literature review. Fuzzy Delphi Method was employed to study the influential factors for evaluation model in every aspect of candidates. Fuzzy Analytic Hierarchy Process was utilized to analyze the weight of each influential factor so as to construct a reasonable and more effective score list, with which a courseware could be evaluated. Based on the given approach, the professional ability on the courseware can be improved and then the teaching quality of the different education field could be upgraded. Besides, the methodology can also be served as a basis for the future development of courseware design.

The validity of the priority vector used in the analytic hierarchy process (AHP) relies on two factors: the selection of a numerical scale and the selection of a prioritization method. The traditional AHP selects only one numerical scale (e.g., the Saaty scale) and one prioritization method (e.g., the eigenvector method) for each particular problem. For this traditional selection approach, there is disagreement on which numerical scale and prioritization method is better in deriving a priority vector. In fact, the best numerical scale and the best prioritization method both rely on the content of the pairwise comparison data provided by the AHP decision makers. By defining a set of concepts regarding the scale function and the linguistic pairwise comparison matrices (LPCMs) of the priority vector and by using LPCMs to unify the format of the input and output of AHP, this paper extends the AHP prioritization process under the 2-tuple fuzzy linguistic model. Based on the extended AHP prioritization process, we present two performance measure criteria to evaluate the effect of the numerical scales and prioritization methods. We also use the performance measure criteria to develop a 2-tuple fuzzy linguistic multicriteria approach to select the best numerical scales and the best prioritization methods for different LPCMs. In this paper, we call this type of selection the individual selection of the numerical scale and prioritization method. We also compare this individual selection with traditional selection by using both random and real data and show better results with individual selection.

Previous researches outlined the advantages of the Analytical Hierarchy Process (AHP) and Analytic Network Process (ANP) methods in solving Multi-Attribute Decision Making (MADM) problems. The advancement of the above methods was continually developed as an effort to cover up various weaknesses. Mainly related to the consistency and linguistic variables in translating the expert opinions. Thus, it initialized the emergence of Fuzzy AHP (F-AHP) and Fuzzy ANP (F-ANP). Due to the restricted operation of these algorithms in smartphone selection, this research attempted to investigate the effectiveness of both methods in providing the analysis of criteria weight, the final recommendation weight, the product recommendation weight, and the execution time in DSS-SmartPhoneRec application development. A survey of one hundred respondents of University students identified the dominant criteria in selecting the smartphone, namely price, Random Access Memory (RAM), processor, internal memory, and camera. Hence, five alternative products were then chosen as the appropriate smartphones’ recommendations based on the respondent’s preferences. As an automatic tool, a DSS-SmartPhoneRec application was built to analyze and compare between F-AHP and F-ANP methods in resolving the smartphone selection cases. It revealed that the level of consistency of criteria weight, the final weight of recommendation, and the weight that the product-based F-ANP was 40% greater than F-AHP. In terms of execution time, F-AHP had a shorter time than F-ANP. Meanwhile, the comparison of products recommendation from DSS-SmartPhoneRec and a manual test showed that F-ANP was 16% more in line with the respondents’ predilection. In a nutshell, the DSS-SmartPhoneRec administered the devote smartphone recommendations based on the user’s expectation. The comparison analysis furnished a learning outcome for the users in determining the appropriate MADM method tailored to the type of cases.

Model to evaluate the state of mechanical equipment based on health value

Article history: Received July 16, 2012 Received in Revised form August, 27, 2012 Accepted 20 September 2012 Available online September 25 2012 Carpet is one of the most popular handcraft industries in Iran and it has created significant number of jobs in various villages and small towns in this country. There are literally many designs and plans introduced by Iranian carpet makers but during the past two decades, we have seen an increasing competition mostly from other countries such as China, India, Pakistan, etc. On the other hands, there are ongoing interests for membership of world trade organization (WTO) and it is necessary to take the necessary actions. The proposed study of this paper uses different mathematical techniques to consider different actions for changing threats to opportunities, reducing unnecessary costs, increasing revenue and market share, etc. The proposed model of this paper uses Fuzzy analytical hierarchy process (AHP), BenefitsOpportunities-Costs-Risks (BOCR) method to detect possible benefit, risk and cost components. We first setup all useful strategies and then using AHP prioritizes different actions. © 2012 Growing Science Ltd. All rights reserved.

The analytic hierarchy process (AHP) approach has been widely applied in multiattribute decision-making situations since being introduced in 1980. It has been believed that the AHP is appropriate to assist decision-making problems characterized by a number of interrelated factors. Recently, a derivative of the AHP, the so-called fuzzy AHP, has been developed by mixing AHP with a fuzzy set theory. This new method increasingly extends its application areas in construction management. Despite extensive use of the fuzzy AHP, little research has been conducted as to the comparability of calculated priority weight vectors by the fuzzy AHP with those by the traditional AHP. Therefore, this paper mainly focuses on the comparison of two AHP approaches by investigating weight vectors produced from a real case study. From the previous studies, four different fuzzy AHP approaches are prepared by applying different fuzzy fundamental scales and weight aggregations, and are tested to identify which method produc...

Ranking of MUDA using AHP and Fuzzy AHP algorithm

Marine Accident investigation multidimensional and complex, so this study aimed to provide a systematic approach to determining the degree of the most influential parameters (dimensions) in accident occurrence in order to improve marine safety in the direction of good governance. In this paper, two-phase procedures are proposed. The first stage utilizes the fuzzy Delphi method (FDM) to determine the critical factors of Marine Accident Investigation by interviewing the pertinent authorities. In the second stage, the fuzzy analytic hierarchy process (FAHP) is applied to pair fuzzy numbers as measurable indices and finally to rank by degree each influential criterion within accident investigation. This study considers 1 goal, 4 aspects, and 31 criteria (parameters) and establishes a ranking model that allows decision-makers to assess the prior ordering of reasons and sort by the most effective parameters involved in marine accident occurrence. The empirical study indicated that People, working and living conditions, effect is considered the highest ranking aspect, and Ability, skills, and knowledge of workers is considered the most important evaluation criterion overall by experts. These results were derived from fuzzy Delphi analytical hierarchy processing (FDAHP). A demonstration of the prior ordering of accident-causing parameters by authorities was addressed as well. Therefore, ranking the priority of every influential criterion (parameter) will help marine transportation decision makers emphasize the areas in which to improve in order to prevent future marine accidents.

Tourism is a dynamic industry that significantly contributes to the global economy, driven by the increasingly diverse preferences of tourists. Addressing these preferences requires sophisticated decision-making models capable of handling the uncertainty and subjectivity of human judgments. This study proposes sustainable models for effectively capturing and evaluating individual tourist preferences using the Analytic Hierarchy Process (AHP) and the Fuzzy Analytic Hierarchy Process (Fuzzy AHP). These models leverage the strengths of the AHP to construct a flexible decision-making framework that adapts to diverse tourist preferences, offering personalized recommendations. In this study, three main criteria are considered: types of tourism, tourism facilities, and tourism areas. Tourists are encouraged to provide their preferences for these criteria and sub-criteria, enabling the AHP and Fuzzy AHP to recommend suitable destinations. An analysis was conducted with 30 respondents providing pairwise comparisons of the tourism criteria, which were then used to generate tourist attraction recommendations using both the AHP and Fuzzy AHP. The study assessed respondents’ satisfaction with the recommendations, finding that both methods were effective, with a slight preference for the Fuzzy AHP due to its ability to better capture individual preferences. The results underscore the potential of these models in sustainably enhancing decision support systems in the tourism industry, offering tailored recommendations that align more closely with tourist expectations.