1,694 research outputs found

    Three Decades of Fuzzy AHP: A Bibliometric Analysis

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    [EN] For decades, Fuzzy Sets Theory (FST) has been consistently developed, and its use has spread across multiple disciplines. In this process of knowledge transfer, fuzzy applications have experienced great diffusion. Among them, Fuzzy Analytic Hierarchy Process (fuzzy AHP) is one of the most widely used methodologies today. This study performs a systematic review following the PRISMA statement and addresses a bibliometric analysis of all articles published on fuzzy AHP in journals indexed in Web of Science, specifically in Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI). The analyzed database includes 2086 articles published between 1994 and 2022. The results show the thematic clusters, the evolution of the academic conversation and the main collaboration networks. The main contribution of this article is to clarify the research agenda on fuzzy AHP. The results of the study allow academics to detect publication opportunities. In addition, the evidence found allows researchers and academics setting the fieldÂżs agenda to advise the editors of high-impact journals on gaps and new research trends.Castello-Sirvent, F.; Meneses-Eraso, C.; Alonso-GĂłmez, J.; Peris-Ortiz, M. (2022). Three Decades of Fuzzy AHP: A Bibliometric Analysis. Axioms. 11(10):1-34. https://doi.org/10.3390/axioms11100525134111

    Fuzzy Analytical Hierarchy Processes for Damage State Assessment of Arch Masonry Bridge

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    The present work proposes a fuzzy analytical hierarchy approach for decision making in the maintenance programming of masonry arch bridges. As a practical case, we propose to classify the degradation state of the Mohammadia masonry bridge. A large number of criteria and sub-criteria are combined to classify this type of bridges through visual inspections. The main criteria (level 1) considered in this work are the history of the bridge, the environmental conditions, the structural capacity and the professional involvement of the bridge. In addition, these criteria are subdivided into several sub-criteria (level 2) which are, in turn, subdivided into sub-criteria (level 3). Considering these criteria and sub-criteria, weights Wiare calculated by fuzzy geometric mean method of Buckley. Subsequently, expert scores were assigned to calculate the overall score CS reflecting the degradation of the considered infrastructure. Thereafter, the masonry arch bridges are classified respecting the French IQOA scoring system using the overall scores value CS. The proposed classification method gave similar results provided by an expert’s study realized previously as part of a national patrimony preservation policy. The obtained results are in good agreement, which makes this method an effective scientific tool for decision-making in view of prioritization of the maintenance after systematic inspection of masonry bridges such as the bridge studied in this work. Doi: 10.28991/cej-2021-03091770 Full Text: PD

    Dry Port Terminal Location Selection by Applying the Hybrid Grey MCDM Model

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    Globalization and decentralization of production generate the intensive growth of goods and transport flows, mostly performed by the maritime transport. Ports, as the main nodes in the global logistics networks, are becoming congested, space for their expansion limited, and traffic in their hinterland congested. As a solution to these and many other hinterland-transport-related problems stands out the development of dry port (DP) terminals. Selection of their location is one of the most important strategic decisions on which depends their competitiveness in the market and the functionality of the logistics network. Accordingly, the evaluation and selection of locations for the development of the DP in accordance with the requirements of various stakeholders is performed in this paper, as a prerequisite for the establishment of an ecological, economic, and socially sustainable logistics network in the observed area. To solve this problem, a new hybrid model of multi-criteria decision-making (MCDM) that combines Delphi, AHP (Analytical Hierarchy Process), and CODAS (Combinative Distance-based Assessment) methods in a grey environment is developed. The main contributions of this paper are the defined model, the problem-solving approach based on finding a compromise solution, simultaneous consideration of the environmental, economic, and social sustainability of the DP concept and its implementation in the regional international markets. The applicability of the approach and the defined MCDM model is demonstrated by solving a real-life case study of ranking the potential DP locations in the Western Balkans region. Based on the obtained results, it is concluded that in the current market conditions, it would be most realistic to open three DP terminals, in Zagreb, Ljubljana, and Belgrad

    Maintenance Strategy Choice Supported by the Failure Rate Function: Application in a Serial Manufacturing Line

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    The purpose of this article is to choose a maintenance procedure for the critical equipment of a forging production line with five machines. The research method is quantitative modelling and simulation. The main research technique includes retrieving time between failure and time to repair data and find the most likely distribution that has produced the data. The most likely failure rate function helps to define the maintenance strategy. The study includes two kinds of maintenance policies, reactive and anticipatory. Reactive policies include emergency and corrective procedures. Anticipatory policies include predictive and preventive ones combined with a total productive maintenance management approach. The most suitable combination for the first three machines is emergency and corrective choice. For the other machines, a combination of total productive maintenance and a predictive approach is optimal. The study encompasses the case of a serial production manufacturing line and maximum likelihood estimation. The failure rate function defines a combination of strategies for each machine. In addition, the study calculates the individual and systemic mean time to failure, mean time to repair, availability, and the most likely number of failures per production order, which follows a Poisson process. The main contribution of the article is a structured method to help define maintenance choices for critical equipment based on empirical data

    Assessment of the agriculture supply chain risks for investments of agricultural small and mediumsized enterprises (SMEs) using the decision support model

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    A key challenge in responding to the emerging challenges in agri-food supply chains is encouraging continued new investment. This is related to the recognition that agricultural production is often a lengthy process requiring ongoing investments that may not produce expected returns for a prolonged period, thereby being highly sensitive tomarket risks. Agricultural productions are generally susceptible to different serious risks such as crop diseases, weather conditions, and pest infections. Many practitioners in this domain, particularly small and medium-sized enterprises (SMEs), have shifted toward digitalization to address such problems. To help with this situation, the current paper develops an integrated decision-making framework, with the Pythagorean fuzzy sets (PFSs), the method for removal effects of criteria (MEREC), the ranksum (RS) and the gained and Lost dominance score (GLDS) termed as PF-MEREC-RS-GLDS approach. In this approach, the PF-MEREC-RS method is applied to compute the subjective and objective weights of the main risks to assess the agriculture supply chain for investments of SMEs, and the PF-GLDS model is used to assess the preferences of enterprises over different the main risks to assess of the agriculture supply chain for investments of SMEs. An empirical case study is taken to evaluate the main risks to assess the agriculture supply chain for SME investments. Also, comparison and sensitivity investigation are made to show the superiority of the developed framework

    Uncertain Multi-Criteria Optimization Problems

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    Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

    Development of an Efficient Planned Maintenance Framework for Marine and Offshore Machinery Operating under Highly Uncertain Environment

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    The constantly increasing complexity of marine and offshore machinery is a consequence of a constant improvement in ship powering, automation, specialisation in cargo transport, new ship types, as well as an effort to make the sea transport more economic. Therefore, the criteria of reliability, availability and maintainability have become very important factors in the process of marine machinery design, operation and maintenance. An important finding from the literature exposed that failure to marine machinery can cause both direct and indirect economic damage with a long-term financial consequence. Notably, many cases of machinery failures reported in databases were as a result of near misses and incidents which are potential accident indicators. Moreover, experience has shown that modelling of past accident events and scenarios can provide insights into how a machinery failure can be subsisted even if it is not avoidable, also a basis for risk analysis of the machinery in order to reveal its vulnerabilities. This research investigates the following modelling approach in order to improve the efficiency of marine and offshore machinery operating under highly uncertain environment. Firstly, this study makes full use of evidential reasoning’s advantage to propose a novel fuzzy evidential reasoning sensitivity analysis method (FER-SAM) to facilitate the assessment of operational uncertainties (trend analysis, family analysis, environmental analysis, design analysis, and human reliability analysis) in ship cranes. Secondly, a fuzzy rule based sensitivity analysis methodology is proposed as a maintenance prediction model for oil-wetted gearbox and bearing with emphasis on ship cranes by formulating a fuzzy logic box (diagnostic table), which provides the ship crane operators with a means to predict possible impending failure without having to dismantle the crane. Thirdly, experience has shown that it is not financially possible to employ all the suggested maintenance strategies in the literature. Thus, this study proposed a fuzzy TOPSIS approach that can help the maintenance engineers to select appropriate strategies aimed at enhancing the performance of the marine and offshore machinery. Finally, the developed models are integrated in order to facilitate a generic planned maintenance framework for robust improvement and management, especially in situations where conventional planned maintenance techniques cannot be implemented with confidence due to data deficiency

    Performance based budget allocation model for water networks

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    ABSTRACT PERFORMANCE-BASED BUDGET ALLOCATION MODEL FOR WATER NETWORKS Mostafa Ismaeel, MASc Concordia University, 2016 The assessment of water network is a challenge that concerns municipalities worldwide. Most of the water distribution systems around the world are deteriorating and, thus, their rehabilitation become urgent while it costs billions of dollars. According to the Canadian Infrastructure Report Card (CIRC, 2016), the Canadian water distribution systems are graded as “good: adequate for now” with 35% graded from “fair” to “very poor” and the estimated replacement cost is almost CAD 60 billion. The American Society of Civil Engineers Report Card has evaluated the condition of drinking water networks in the United States as “poor” with a grade “D”, stating that the United States water networks need USD 126 billion in order to reach a grade “B” by 2020 (ASCE, 2013). Thus, it is obvious that the necessity of providing continuous potable water under tight budgets plunks extra pressure on municipalities and triggers the need for a proper performance assessment. Accordingly, this research aims at developing a Water Networks Performance-Based Budget Allocation (WNPBA) model, composed of two sub-models: (1) Water Networks Performance Assessment (WNPA) model to precisely assess the performance of the water network components and (2) Budget Allocation (BA) model to optimally allocate budget according to the performance assessment. The WNPA model encompasses two key indices: (1) Pipes Performance Index (PPI) and (2) Accessories Performance Index (API). These indices reflect the status of network components and their deterioration levels and they propose consequent, preventative actions. The WNPA utilize the Fuzzy Analytical Network Process (FANP) to identify and evaluate the weight of functional performance criteria (i.e. physical, operational, quality of service and environmental) of pipes and accessories. It also exploits both the Preference Ranking Organization Method of Enrichment Evaluation (PROMETHEE) and the simple Multi Attribute Utility Theory (MAUT) to compute the functional and global performance indices of the network components. Moreover, the BA model utilize genetic algorithms (GA) and Greedy Heuristics (GH) to optimally allocate the available funds. The required data for this research is collected from experts and two water municipalities (Montreal, QC and Moncton, NB). The developed models are applied to the two water networks. The results show that most of City of Moncton sub-network 2 components are in a good or medium state, except for pipes 4 & 10 and accessory 7; those are in a poor state, while sub-network 1 is graded excellent for 1 accessory, good for 9 accessories and 7 pipes, medium for 23 accessories and 14 pipes and poor for 2 accessories and 14 pipes. The pipelines in city of Montreal sub-network are graded excellent for 16 pipes, good for 32 pipes and medium for 5 pipes while the accessories are graded excellent for 49 accessories, medium for 8 accessories and poor for 21 accessories. All the sub-networks are generally in a medium state (4<PI≤6). City of Moncton results are verified where the verification factor (VF) is found to be higher than 0.8. Results from the city of Montreal are verified, where almost 90% of the recommended actions from the budget allocation match the actions recommended by the city of Montreal water services. Thus, it can be concluded that WNPBA has proved to be a promising tool with a high capacity in allocating budget to water network components, based on performance indices. Finally, the developed models helps maintain the water supply healthy and work continuously, while maintaining the network in an acceptable condition and protecting it against any unexpected incidents
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