Integrated Fuzzy Analytic Hierarchy Process Research Articles

Integrated approach for occupational health and safety (OHS) risk Assessment: An Empirical (Case) study in Small enterprises

Like large and medium industries, Occupational Health and Safety (OHS) management has become a highly demanding issue for Small Enterprises (SEs) under the backdrop of numerous and varied diseases and accidents. However, any systematic OHS risk assessment model is still lacking in SEs. This study is initiated to develop a comprehensive model by integrating Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Inference System (FIS). A total of 16 sub-criteria under 3 criteria were chosen using focus group discussions with several experts. The weights of the sub-criteria were determined using FAHP method, which were further used to score the present conditions of the SEs. Three input variables and one output variable were selected for generating FIS model. The FIS model for OHS risk assessment was established after constructing fuzzy membership functions and fuzzy inference rules.This model was implemented in five SEs of Bangladesh for validation. The risk scores were calculated and among the five enterprises, one was found highly risky, and three were moderately risky. Expectedly, this model will assist the safety professionals and managers to design effective workplace health and safety management strategy and programs.

An Integrated Fuzzy Analytic Hierarchy Process (AHP) Model for Studying Significant Factors Associated with Frequent Lane Changing.

Frequent lane changes cause serious traffic safety concerns, which involve fatalities and serious injuries. This phenomenon is affected by several significant factors related to road safety. The detection and classification of significant factors affecting lane changing could help reduce frequent lane changing risk. The principal objective of this research is to estimate and prioritize the nominated crucial criteria and sub-criteria based on participants’ answers on a designated questionnaire survey. In doing so, this paper constructs a hierarchical lane-change model based on the concept of the analytic hierarchy process (AHP) with two levels of the most concerning attributes. Accordingly, the fuzzy analytic hierarchy process (FAHP) procedure was applied utilizing fuzzy scale to evaluate precisely the most influential factors affecting lane changing, which will decrease uncertainty in the evaluation process. Based on the final measured weights for level 1, FAHP model estimation results revealed that the most influential variable affecting lane-changing is ‘traffic characteristics’. In contrast, compared to other specified factors, ‘light conditions’ was found to be the least critical factor related to driver lane-change maneuvers. For level 2, the FAHP model results showed ‘traffic volume’ as the most critical factor influencing the lane changes operations, followed by ‘speed’. The objectivity of the model was supported by sensitivity analyses that examined a range for weights’ values and those corresponding to alternative values. Based on the evaluated results, stakeholders can determine strategic policy by considering and placing more emphasis on the highlighted risk factors associated with lane changing to improve road safety. In conclusion, the finding provides the usefulness of the fuzzy analytic hierarchy process to review lane-changing risks for road safety.

SUPPLIER SELECTION AMONG DIFFERENT SCALE CONSTRUCTION COMPANIES USING FUZZY AHP AND FUZZY TOPSIS

Supplier selection is an important strategic decision for construction companies due to long-term project durations and high costs. In the construction sector, supplier selection decisions should take several criteria and alternatives into account. Along with the high number of alternative suppliers, choosing the best method to evaluate the alternative suppliers is another critical step. In this study, we compare the effectiveness of different multi-criteria decision‐making methods for selecting the most convenient supplier for construction companies. In this respect, we study the integration of powerful multi-criteria decision‐making methods, Fuzzy Analytic Hierarchy Process (AHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). We use Fuzzy AHP for the calculation of decision criteria weights, and then we apply Fuzzy TOPSIS for ranking the alternatives. Several interviews were made with the experts at construction companies and as a result of those interviews, 7 main criteria and 24 sub-criteria for comparing alternative suppliers of the companies were determined. We test our approach for two construction companies and use an integrated Fuzzy AHP and Fuzzy TOPSIS method to find the best supplier for the selected criteria. The contribution of this study is not limited to the multi-criteria decision-making methods for the supplier selection problem in the construction sector, but also we make a comparison of the supplier selection decisions of two different sized companies having the same supplier pool, and we show the effect of company based criteria weights in supplier selection.

Integrated Fuzzy Analytic Hierarchy Process and Technique for Order of Preference by Similarity to Ideal Solution for Additive Manufacturing Printer Selection

Integrated Fuzzy Analytic Hierarchy Process and Technique for Order of Preference by Similarity to Ideal Solution for Additive Manufacturing Printer Selection

Performance analysis of fuzzy analytic hierarchy process multi-criteria decision support models for contractor selection

Multi-Criteria Decision Making (MCDM) is a discipline aimed at supporting decision-makers to settle on an ideal choice within the sight of different and clashing criteria. MCDM strategies have developed to oblige different kinds of utilizations. One comprehensively utilized MCDM strategy is the Analytic Hierarchy Process (AHP). AHP, in spite of its simplicity in idea, it can't consider imprecise input. Throughout the years, fuzzy logic has demonstrated its effectiveness as a MCDM technique. It includes a few preferences inside uncertain, imprecise and obscure settings than AHP and other MCDM strategies. Consolidating Fuzzy strategies with AHP is one methodology for taking care of the entangled issues of AHP. The significance of this study is to provide baseline information to the construction clients and consultants on the importance of contractor's prequalification decision criteria to be adopted, which will eventually translate to a better decision making and increase project performance. Taking into account our past research, this paper proposed a Feedback Integrated Fuzzy Analytic Hierarchy Process (FAHP) model for ranking decision criteria for contractual worker determination by combining the selection process and consistency control module. This consistency control module contains a feedback module that generates advice to decision makers so as to check the irregularity in their decisions' during pairwise comparisons. In this paper, the performance investigation of the proposed FAHP model is validated on datasets from three diverse FAHP models. The proposed model accuracy obtained when tested with three distinctive datasets were 98.2%, 99.99%, and 98.24% respectively. The results established the adequacy and uselfulness of the proposed FAHP model in ranking contractor decision criteria. The research additionally guide decision-makers on picking distinctive FAHP algorithms in assessing and ranking decision criteria utilized in contractors selection.

Earthquake risk assessment using an integrated Fuzzy Analytic Hierarchy Process with Artificial Neural Networks based on GIS: A case study of Sanandaj in Iran

Earthquakes are natural phenomena, which induce natural hazard that seriously threatens urban areas, despite significant advances in retrofitting urban buildings and enhancing the knowledge and ability of experts in natural disaster control. Iran is one of the most seismically active countries in the world. The purpose of this study was to evaluate and analyze the extent of earthquake vulnerability in relation to demographic, environmental, and physical criteria. An earthquake risk assessment (ERA) map was created by using a Fuzzy-Analytic Hierarchy Process coupled with an Artificial Neural Networks (FAHP-ANN) model generating five vulnerability classes. Combining the application of a FAHP-ANN with a geographic information system (GIS) enabled to assign weights to the layers of the earthquake vulnerability criteria. The model was applied to Sanandaj City in Iran, located in the seismically active Sanandaj-Sirjan zone which is frequently affected by devastating earthquakes. The Multilayer Perceptron (MLP) model was implemented in the IDRISI software and 250 points were validated for grades 0 and 1. The validation process revealed that the proposed model can produce an earthquake probability map with an accuracy of 95%. A comparison of the results attained by using a FAHP, AHP and MLP model shows that the hybrid FAHP-ANN model proved flexible and reliable when generating the ERA map. The FAHP-ANN model accurately identified the highest earthquake vulnerability in densely populated areas with dilapidated building infrastructure. The findings of this study are useful for decision makers with a scientific basis to develop earthquake risk management strategies.

A novel pythagorean fuzzy AHP and TOPSIS method for the wind power farm location selection problem

This paper proposes an Integrated Fuzzy Analytic Hierarchy Process (AHP) with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method using Pythagorean fuzzy sets for the wind farm location selection problem. The method combines the advantages of the two methodologies to consider uncertainties and lack of information in the decision-making process (human expert capacities) and enables better representation of membership and non-membership functions, and at the same time, allows for the evaluation of large numbers of alternatives and criteria. The authors implement the method to evaluate four potential sites near cities located in the west and north-west regions of Turkey, using seven main criteria and twenty-five sub-criteria. The analyses are based on the judgements of three experts/decision-makers. Moreover, the authors compare the results (site ranking) of the methodology, with those from a Pythagorean Fuzzy AHP and an interval-valued Type-2 fuzzy AHP method. With the additional consideration of the sub-criteria, the proposed method generates slight differences in the ranking compared to the previously evaluated methods.

A hybrid mathematical programming model for optimal project portfolio selection using fuzzy inference system and analytic hierarchy process

The primary goal in project portfolio management is to select and manage the optimal set of projects that contribute the maximum in business value. However, selecting Information Technology (IT) projects is a difficult task due to the complexities and uncertainties inherent in the strategic-operational nature of the process, and the existence of both quantitative and qualitative criteria. We propose a two-stage process to select an optimal project portfolio with the aim of maximizing project benefits and minimizing project risks. We construct a two-stage hybrid mathematical programming model by integrating Fuzzy Analytic Hierarchy Process (FAHP) with Fuzzy Inference System (FIS). This hybrid framework provides the ability to consider both the quantitative and qualitative criteria while considering budget constraints and project risks. We also present a real-world case study in the cybersecurity industry to exhibit the applicability and demonstrate the efficacy of our proposed method.

An Integrated Fuzzy AHP and Fuzzy TOPSIS Approach to Assess Sustainable Urban Development in an Emerging Economy.

Sustainable urban development (SUD) requires a balance between economic growth, social well-being, and environmental protection. Oftentimes, urban policy makers can hardly fulfill all SUD goals due to inadequacy of resources to support SUD programs. Therefore, the process of allocating scarce resources to achieve and balance various SUD goals becomes a critical challenge for policy makers and researchers. To solve this problem, this study adopts fuzzy Analytic Hierarchy Process (AHP) and fuzzy Technique for Order Preference by Similarity to Ideal Situation (TOPSIS) to assess and rank different indicators of SUD and evaluate different cities in an emerging economy (Vietnam). Fuzzy methods exhibit more advantages than traditional ranking methods. Fuzzy AHP is an extension of AHP, whereas fuzzy TOPSIS is an extension of TOPSIS. Fuzzy methods are used to overcome disadvantages of traditional methods and are beneficial techniques for solving complicated decision problems with a realistic solution. Using a valid sample data of ten experts in the field of SUD, empirical results show that education, healthcare, quality of life, and social democracy are the most important indicators of SUD. By contrast, social diversity, social maturity, and energy consumption are the least important indicators of SUD. For social sustainability, social democracy and quality of life are the two most important criteria, whereas social maturity and social diversity are the two least important criteria. For economic sustainability, education and healthcare are the two most important criteria, whereas infrastructure and income are the two least important criteria. For environmental sustainability, water quality and waste disposal are the two most important criteria, whereas energy consumption and ecological conservation are the two least important criteria. Furthermore, fuzzy TOPSIS results reveal the best and the worst cities in Vietnam with regard to overall SUD and its three components. This study provides evidence for researchers and policy makers to better understand the importance of different goals of SUD and efficiently allocate scarce resources to achieve and balance different SUD goals. Furthermore, researchers and policy makers should further focus on indicators such as social democracy, quality of life, education, healthcare, water quality, and waste disposal. These indicators will help obtain the goals of SUD.

Measuring the Sustainable-Security of Web Applications Through a Fuzzy-Based Integrated Approach of AHP and TOPSIS

Ensuring sustainable-security of web applications for minimizing security breaches and enhancing users' trust and satisfaction is the foremost priority of all security experts and web developers. However, sustainable-security is multidimensional, emergent, and an irreducible concept. Also, designing sustainable-security of web application is a complex process because it is a multi-attribute approach which is based on the users' needs and organization's policies. In this context, the decision making process could be an effective means to quantitatively evaluate sustainable-security of web application design. In this research study, the authors have used a technique that involves integrating Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) approaches for the assessment of sustainable-security of web applications. The efficacy of this technique has then been tested on a web application designed specifically to cater to the requisites of an academic institution, Babasaheb Bhimrao Ambedkar University in India. Given the sensitivity of web application, this paper has used different versions of a University web application. The results thus obtained and the approach employed in this study would definitely aid the future researchers and developers in designing web applications with higher sustainable-security.

PERSONNEL SELECTION FOR PROMOTION USING AN INTEGRATED FUZZY ANALYTIC HIERARCHY PROCESS-GREY RELATIONAL ANALYSIS METHODOLOGY: A REAL CASE STUDY

The basic idea of personnel selection is to choose the best candidate for a job. Personnel selection is crucial in human resources management and also a very important issue for both academicians and industrialists. Personnel selection can be handled as a Multi Criteria Decision Making (MCDM) problem. The aim of this paper is to determine the best personnel using the integrated Fuzzy Analytic Hierarchy Process (FAHP) and Grey Relational Analysis (GRA) methodology. FAHP is used to determine the importance weights of personnel (17 alternatives) according to personnel selection criteria (22 subcriteria are categorized under 5 main criteria). Then, obtained fuzzy importance weights defuzzified by centroid method. After that, defuzzified importance weights of personnel according to personnel selection criteria are integrated with a GRA model to prioritize the personnel alternatives. For a case study in Turkey, the ranking of the alternatives is calculated using the integrated FAHP-GRA model, and the best-performing personnel is selected for promotion. According to this methodology, managers/human resources department can easily predict how they can evaluate and promote employees. The proposed methodology provides less data and can analyze many factors that can overcome the disadvantages of statistics methods in the literature. The main contribution of this study is to reduce data for a preference matrix using the integrated methodology. As a result, the number of transactions decrease. To the authors’ knowledge, this will be the first study which integrates Fuzzy Analytic Hierarchy Process (FAHP) and Grey Relational Analysis (GRA) methodologies for human resources in the area of industrial engineering.

Construction Projects Assessment Based on the Sustainable Development Criteria by an Integrated Fuzzy AHP and Improved GRA Model

Due to the increasing population and earth pollution, managing construction and infrastructure projects with less damage to the environment and less pollution is very important. Sustainable development aims at reducing damage to the environment, making projects economical, and increasing comfort and social justice. This study proposes fuzzy analytic hierarchy process (AHP) and improved grey relational analysis (GRA) to assess construction projects based on the sustainable development criteria. For doing so, sustainable development criteria are first identified in economic, social, and environmental dimensions using literature review, and are then customized for urban construction projects using experts’ opinions. After designing questionnaires and collecting data, fuzzy AHP is used for determining the importance of sustainable development criteria and their subcriteria. Then, improved GRA is employed for assessing six recreational, commercial, and official centers in Isfahan regarding the weights of criteria and subcriteria. The proposed fuzzy AHP-improved GRA help us to prioritize construction projects based on the sustainable development criteria. The results of applying fuzzy AHP show that the weights of economic, social, and environmental criteria are equal to 0.330, 0.321, and 0.349, respectively, which are close to each other. This means that the importance of all three aspects of sustainability is almost equal to each other. Furthermore, “Having profits for the society”, “Increasing social justice”, and “Adherence to environmental policies” are identified as the most important indicators of sustainable development in terms of economic, social, and environmental aspects, respectively. Finally, the results of employing improved GRA determine Negin Chaharbagh recreational and commercial complex as the best project.

Fire probability prediction of offshore platform based on Dynamic Bayesian Network

By integrating Markov model with Bayesian Network, an improved Dynamic Bayesian Network (DBN) model is proposed in this paper. It could be used to predict the dynamic probability of offshore platform fire. It is a new stochastic model which could process dynamic data. Three innovations are achieved in building this model. Firstly, a modified Human Factor Analysis and Classification System (HFACS) model is used to provide guidance for the construction of BN in describing the sequence of causes for offshore platform fire. Secondly, the prior probability is determined by using Evidence Theory model based on historical data. Thirdly, the conditional probability table of basic events is calculated by integrating Fuzzy Analytic Hierarchy Process (AHP) with Hierarchical Node Distance Formula. Lastly, the transition probability of BN is obtained based on Markov model. There are three major functions of the new model. First of all, through forward reasoning, the dynamic probabilities of platform fire at different time are obtained. Second, based on the diagnosis reasoning, the impact of human and organizational factors on the fire is researched. Last, the sensitivity analysis and uncertainty analysis of human, organizational and equipment factors are also researched to identify the significant causes and to quantify the effect.

An integrated fuzzy multi-criteria group decision making approach for project delivery system selection

The success or failure of a project depends on the adoption of a suitable Project Delivery System (PDS). This paper presents an integrated Fuzzy AHP Multi- Criteria Group Decision Making (FMCGDM) approach for the project delivery system selection. The proposed approach can select the best PDS option based on the opinions of a heterogeneous group of experts. The relative weights of decision criteria as well as their scores are evaluated using Analytic Hierarchy Process (AHP) technique. The criteria weights and scores assigned by di erent decision makers are aggregated and converted to a fuzzy number. The relative weight of decision makers is determined using a new fuzzy logic based method. Finally, the score of each PDS option is determined as a fuzzy number by the use of Zadeh's extension principle and performing interval arithmetic at discrete -cuts. To evaluate the performance of the proposed method, it is implemented on a real dam and hydropower plant project.

Evaluation of Design Alternatives’ Environmental Impact by Integrating Fuzzy Analytic Hierarchy Process and Evidential Reasoning Approach

Today “ecodesign” is a necessary consideration in the product development process. With increasing general awareness of the need for environmental production and more stringent regulatory requirements, manufacturers have to try to minimize their environmental impact. Life-cycle assessment (LCA) methodology is a generally accepted quantitative approach that can be applied to support environmental impact evaluations of a product. However, despite the time-consuming and resource-consuming attributes of the LCA, it has difficulty to deal with uncertain information. Therefore, LCA is yet to be a practical approach for environmental impact evaluation, particularly, during new product development (NPD). This paper proposes an approach to evaluate the environmental performance of design alternatives during NPD. The use of multiple criteria decision-making (MCDM) approaches with LCA methodology for the evaluation of design alternatives’ environmental performance during NPD processes is first discussed. The proposed approach integrates analytic hierarchy process (AHP) and fuzzy set theory (FST) with evidential reasoning (ER) in the evaluation of environmental performance to prioritize different design options. A case study is described to illustrate the use of the proposed method.

Integrated Fuzzy AHP–TOPSIS for selecting the best plastic recycling method: A case study

Due to the rapid depletion of natural resources and undesired environmental changes in a global scale, it is necessary to conserve the natural resources and protect the environment. Industries which manufacture plastic based products have the necessity to recycle plastics. There are number of methods to recycle plastics. Since the selection of the best recycling method involves complex decision variables, it is considered to be a multiple criteria decision-making (MCDM) problem. This article develops an evaluation model based on the fuzzy Analytic Hierarchy Process (AHP) and the technique for order performance by similarity to ideal solution (TOPSIS) to enable the industry practitioners to perform performance evaluation in a fuzzy environment. The purpose of the study is to determine the best method for recycling plastics among the various plastic recycling processes. By observing the results, it is identified that mechanical recycling process is found to be the best plastic recycling process using the integrated approach.

Integrating fuzzy analytic hierarchy process with PROMETHEE method for total quality management consultant selection

Evaluation of the proper and appropriate consultants can play an important role in successful total quality management (TQM) program implementation and helps the manufacturing organizations to attain competitive advantage. In general, many conflicting factors affect the appropriate consultant selection problem which adheres to uncertain and imprecise data. In this paper, a simple, systematic and logical scientific approach is structured to evaluate TQM consultant through integrating Fuzzy Analytical Hierarchy Process with the Preference Ranking Organization Method for Enrichment Evaluations. The proposed decision-making approach takes advantage of the synergy between these two well-known multi-criteria decision-making methods in which their strong and weak points are detected and a ranking is provided which facilitates the final selection for the decision-maker. To accredit the proposed model, it is implemented in a furniture industry in Bangladesh. The results indicate that technical/administrative is the most significant criteria whereas work experience in related field is the most important sub-criteria.