Multi-criteria Decision-making Approach Research Articles

Selection of optimal seismic intensity measures using fuzzy-probabilistic seismic demand analysis and fuzzy multi-criteria decision approach

A fuzzy decision-theoretic computational approach for selecting optimal intensity measures (IMs) under the conditions of randomness, fuzziness and uncertainty is proposed in this paper. The main objectives of this study are twofold: (a) to quantify the contribution of multiple evaluation criteria, and (b) to improve the credibility of decision-making results by selecting the appropriate multi-criteria decision making (MCDM) method. To achieve these, three components of the methodology for this approach are utilized: (1) Fuzzy-probabilistic seismic demand analysis (FPSDA) is employed to consider the aleatory and epistemic uncertainties in the seismic demand analysis. (2) Fuzzy analytical hierarchical process (FAHP) is used to determine the importance weights of multiple evaluation criteria. (3) A combination of FAHP and fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) is utilized to determine the optimal IM alternatives. First, the FPSDA method in which the interval PSDA is applied to evaluate the IM performance is developed. The interval results are transformed into triangular fuzzy numbers to establish a fuzzy decision-making matrix. Subsequently, the FAHP is employed to estimate the importance of each evaluation criterion. Then, FAHP–FTOPSIS is utilized to rank the orders of the IM alternatives and select the optimal IM. An illustrative application of the proposed methodology to a five-story reinforced concrete frame structure is presented. The decision results demonstrate that by considering the maximum inter-story displacement angle (θmax), top displacement (Dt), maximum floor velocity (Vmax) and maximum floor acceleration (Amax) as engineering demand parameters (EDPs), the average spectral displacement (Sdam), Sdam, average spectral velocity (Svam), and Vamvatsikos spectral acceleration (VSa2) are the most optimal IMs, respectively. The decision-making results for multiple EDPs indicate that Svam is the optimal IM. Furthermore, the Cordova spectral acceleration (CSa) considering period prolongation has the highest closeness coefficient among the acceleration-related IMs. To verify the effectiveness of the new framework and methodology, the performance of the proposed approach is compared with that of the traditional MCDM method while ignoring fuzziness. The proposed methodology can be applied to other engineering structures and provide a reference for solving similar problems.

A New Approach for Failure Modes, Effects, and Criticality Analysis Using ExJ-PSI Model—A Case Study on Boiler System

Failure Modes, Effects, and Criticality Analysis are widely used to assess the failure modes of a system, along with their causes and effects. Several Multi-Criteria Decision-Making approaches have been developed to overcome the limitations of the traditional FMECA. In these approaches, several multiple criteria are considered to determine the criticality values and assign criticality ranks. In these developed approaches, only one expert can involve in criticality analysis. By incorporating several experts from design, manufacturing, and maintenance domains in the criticality analysis accuracy of the results can be improved. This paper proposes a new integrated Expert Judgment-based Preference Section Index (ExJ-PSI) model that combines MCDM approaches and integrates expert opinions. The proposed model is applied to a boiler system used in the textile industry. The results are compared with those obtained from the conventional FMECA and normalized median method. In the present study, the opinions of seven experts from various domains and organizations are discussed. To normalize the collected data, one scale is developed by considering four expert criteria, such as the experience of the expert, the number of boilers he is handling, the number of employees under his supervision, and the proficiency in the field. The proposed model is more effective and flexible in handling and analyzing data of complex configured systems consisting of many subsystems, components, and failure modes. The analysis reveals that the feed water pump, feed water pump motor, supply water temperature sensor, return water temperature sensor, header, and coal feed motor are some of the most critical components of the boiler system.

Selecting suitable wave energy technology for sustainable development, an MCDM approach

Considering sustainable development, technology selection is a multi-criteria decision-making (MCDM) problem that influences the advantages of enterprises or a country. This paper investigates existing wave energy technologies as alternatives to green and sustainable technologies to apply them in the seas and oceans. A framework is presented, and major technologies to extract wave energy are identified. Each technology has been examined in scopes of strategic factors, availability, technical knowledge, technological features, economic, social, and environmental factors as the main criteria. Totally, 20 converters and 52 criteria are considered. The Caspian Sea is considered as a case, and a decision matrix is established by integrating the gathered data and the experts’ opinions. By integrating the fuzzy Delphi method (FDM) and preference ranking organization method for enrichment evaluations (PROMETHEE) method, Pelamis is considered the most appropriate technology to harvest wave energy in the Caspian Sea.

Determination of a maintenance strategy for machinery systems of autonomous ships

This paper proposes a hybrid multi-criteria decision-making approach to determine the best maintenance strategy for the machinery systems in autonomous ships of different levels of autonomy. The proposed methodology includes the Analytic Hierarchy Process to identify criteria weighting and the Technique for Order of Preference by Similarity to Ideal Solution to determine the best maintenance alternative. A sensitivity analysis is conducted to determine the impact of criterion weighting on the calculated rank scores and to reveal the criticality of the criteria. The study presents and considers various hybrid maintenance strategies for autonomous ship concepts as possible maintenance alternatives. The selection of the maintenance policy that combines condition-based and time-based approaches for 3rd and 4th levels of ship autonomy, as the best maintenance alternative, demonstrates the basic idea of the study. In addition, the key findings of the paper ensure crucial insights to the maritime industry in the decision-making process on the maintenance strategy that can be adapted to different types of autonomous ship concepts.

A novel hybrid MCDM approach to evaluate universities based on student perspective.

University rankings are an essential source of comparisons between universities according to specific combinations of criteria. International or national rankings have an increasing impact on higher education institutions, stakeholders, and their environments. Thereby, on behalf of effective decision-making, university-ranking efforts should be a process involving some conflicting criteria and uncertainties in a more sensitive manner. This study presents a detailed university evaluation procedure under certain service criteria via multi-criteria decision-making (MCDM) methodologies and provides an appropriate clustering of universities according to teaching and research factors. A hierarchical cluster-based Interval Valued Neutrosophic Analytic Hierarchy Process (IVN-AHP) integrated VIKOR methodology that includes two stages, clustering and ranking, is proposed for the university evaluation problem. The hierarchical clustering method is performed using teaching and research factors in the first stage. The second stage addresses the determination weights of service criteria through IVN-AHP and the ranking of universities by using VIKOR according to service criteria under determined clusters. This study, in which the proposed methodology is applied to Turkish universities, is the most comprehensive in terms of the number of universitiesevaluated and participating students. Furthermore, the integration of IVN-AHP and VIKOR to solve MCDM problems is presented for the first time. This study differs from other studies in terms of novelties both methodological-based and application based. Moreover, categorizing universities with similar characteristics into groups using cluster analysis and ranking them with the MCDM methodology provide a more realistic and effective interpretation of the results.

Linking the trust of industrial entrepreneurs on elements of ecosystem with entrepreneurial success: Determining startup behavior as mediator and entrepreneurial strategy as moderator.

This study aimed to apply "multi-criteria decision approach and attitude-change theory" to examine post-COVID-19 impact on entrepreneurial mindset by investigating the link between entrepreneurs social capital (trust on three elements of ecosystem i.e., experts & enterprises, media, and government) and entrepreneurial success (both individual and organizational). Specifically, this study analyzed entrepreneurs' dispositional factor (startup behavior) as an underlying mechanism to bridge trust and entrepreneurial success. Furthermore, it also analyzed entrepreneurs' situational factor (entrepreneurial strategy) as boundary condition. We applied time-lagged data collection from 505 industrial entrepreneurs. Survey method was used for data collection. A 7-point Likert scale was used for the respondent response. Hayes developed PROCESS models 4 and 7 were used to test the hypothesis. The direct impact of trust on three elements of the ecosystem was found significantly positive on both startup behavior and entrepreneurial success. The direct impact of startup behavior on entrepreneurial success is also significantly positive. The impact of startup behavior on indirect mediation between trust and entrepreneurial success is visibly positive. The moderated and moderated mediation impact of entrepreneurial strategy found positively significant at low and medium values. However, this study found an insignificant moderated impact at high values of entrepreneurial strategy between trust on media and startup behavior. Furthermore, this study also found insignificant moderated mediation impact at high values of entrepreneurial strategy by interacting with two elements of ecosystem (trust on media and trust on government) through startup behavior on entrepreneurial success. The authors suggested that startup behavior is an underlying mechanism through which industrial entrepreneurs trust achieved desired entrepreneurial success. The authors also suggested that the influencing role of "low level of entrepreneurial strategy" in comparison with "high level entrepreneurial strategy" is more helpful to achieve entrepreneurial success. This study contributed to the literature on entrepreneurial strategy for its conditional indirect moderated impact on startup behavior and moderated mediation impact on firm entrepreneurial success. It also contributed to owners of the manufacturing industry for their startup behavior as an underlying mechanism through which trust influences entrepreneurial success.

Evaluate land suitability analysis for rice cultivation using a GIS-based AHP multi-criteria decision-making approach: Majalengka Regency, West Java Province

This research is motivated by the agricultural sector ranks first and plays a vital role in GRDP income in Majalengka Regency. This study aims to predict areas suitable for land use for sustainable food agriculture (LP2B) and evaluate land suitability for rice. We use the Analytical Hierarchical Process (AHP), and Geography Information System (GIS) approaches to give weight to the suitability of criteria and sub-criteria that influence multi-criteria decisions. Including using parameters; Soil morphology, elevation, rainfall, water cover, land area, disaster risk, erosion, and slope are the criteria identified as requirements for the intended application. The resulting weights to build a suitability map layer using a weighted sum overlay tool on a GIS platform by involving government stakeholders in Majalengka Regency. The results showed that the map of the evaluation of the suitability of rice production in the study area with the land was very suitable, namely 11% (15,038.49 ha) of the total study area, which was very suitable for rice production. The relationship between suitability maps and changes in spatial patterns in 2022 in the study area has also overlapped. The results showed the suitability of the spatial plan with the results of the suitability map of paddy fields.

Implementation of integrated BIM-VR into construction management curriculum: lessons learned and development of a decision support system

Several educational institutions and universities have introduced Building Information Modelling (BIM) and Virtual Reality (VR) courses separately in the construction management (CM) programs around the globe, and others are in the process of integrating them into their curricula. However, fewer institutions have included integrated BIM and VR into their courses. The industry needs for integrated BIM-VR are not fully recognised by universities due to the lack of a guideline and cognitive dissonance between academia and industry. As a result, most universities do not have a rigorous strategy for developing BIM-VR teaching topics and plans. This study firstly aims to report on some of the employed processes by university lecturers and academics in an Australian University to integrate BIM-VR education into CM curriculum. The review on the secondary sources indicates that the integration of BIM/VR education requires the consideration of three aspects including: industry needs, course contents, classroom size and software and hardware selection. The second aim of this paper is to develop a decision support system by utilising the PROMETHEE method as one of the multi-criteria decision-making approaches. The findings of the secondary sources and development of the decision support system help the educational institutions and practitioners for their future BIM-VR implementation initiatives.

Decision support framework for inventory management combining fuzzy multicriteria methods, genetic algorithm, and artificial neural network

Decision support tools, within the Industry 4.0 perspective, have increasingly impacted different operations and supply chain management (OSCM) areas, such as inventory management. Within the digital transformation era, multicriteria decision-making (MCDM) and machine learning (ML) can be used to improve inventory management decisions. Despite their importance, the literature lacks empirical studies involving advanced solutions that combine both approaches to support practitioners in real-life settings. This is especially relevant for maintenance, repair, and operation (MRO) inventories, which usually present several SKUs with irregular demand patterns and difficult forecasting. Therefore, this study proposes a decision support framework for inventory management, combining MCDM and ML approaches, and applies it to a railway logistics operator to assist its MRO inventory management decision-making process. The first stage of the framework consists of applying a hybrid MCDM method that combines fuzzy logic with the analytic hierarchy process (AHP) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methods to rank and select SKUs according to importance and criticality. Once the most critical SKUs are revealed, a second stage of the framework is introduced to forecast the demand for these SKUs through an ML model, which combines a genetic algorithm and an artificial neural network (GA-ANN). Research findings point to a considerable improvement in the accuracy of the demand forecast for SKUs compared to the previous forecast by the company, and the forecasting methods support vector machine (SVM) and exponential smoothing. The results of the combined approaches are consolidated into a management dashboard, which improves the agility and quality of the analyzed company's decision-making process in inventory management. Therefore, practitioners can also take stock of the proposed framework as a semi-automatic management artefact to enhance decision-making from a digital transformation view in a vital area of OSCM.

Purchase decision making of garage equipment using an integrated fuzzy AHP and grey relation analysis method

PurposeAutomobile maintenance garages require varieties of equipment for their smooth functioning. However, the purchase of the right equipment from alternatives is a tough task as it depends on several economic, technical, and environmental considerations, etc. Moreover, there are different sellers for such equipment, whose features would be satisfying the purchase criteria in varying levels or degrees. Hence, this purchase decision becomes a complex decision-making problem.Design/methodology/approachAn integrated multi-criteria decision-making approach that includes the combination of fuzzy AHP (analytic hierarchy process) and GRA (grey relational analysis) is used for the purchase decision-making of garage equipment. Various purchase decision criteria regarding garage equipment are assimilated through literature and interaction with garage professionals. The weightage of each purchase criteria of garage equipment is derived using fuzzy AHP. After the establishment of weights, various equipment suppliers are evaluated according to their conformance to the criteria using the GRA method.FindingsThe methodology of FAHP helped in ranking the different purchasing criteria based on their importance. It follows the following sequence: cost of ownership, technical specifications, operational characteristics, reliability and maintenance, after-sales support, commercial features, environmental pollution, and end of life characteristics. GRA methodology has been applied for the purchase of the best common rail test bench among alternatives according to their fulfillment of the purchase criteria requirements that are evaluated by a team of experts.Originality/valueThe integrated approach developed in this work for garage equipment purchase will help garage management to prioritize each supplier of the equipment based on their level of conformance to the purchase criteria.

Digitalization strategies and evaluation of maritime container supply chains

PurposeThis study proposes practical digitalization strategies and well-grounded evaluation criteria for maritime container supply chains.Design/methodology/approachThe authors identified the status of supply chain digitalization of the Port of Busan in South Korea and developed three digitalization strategies based on industry requirements and consultations with port experts. The authors proposed 11 evaluation criteria for examining the main digitalization strategies in the supply chain operations reference model, based on a survey among 46 experts and used multi-criteria decision-making approaches to prioritize the strategies and evaluation criteria.FindingsThe results delineate the status of the digitalization of a real-world port-focal supply chain. The model can be successfully customized to include well-grounded evaluation criteria for digitalization strategies, and presents a practical way to advance the supply chain digitalization strategies. Based on the survey and evaluation, the authors find that increasing data accessibility and improving quality are preferred to adopting a data and information sharing platform.Research limitations/implicationsAs the study is limited to the Port of Busan, future case studies could be undertaken to container supply chains driven by different regional ports.Practical implicationsStakeholders, such as truckers, terminal operators, and shipping liners, might consider the proposed strategies and evaluation criteria when digitalizing their supply chains.Originality/valueBy identifying the needs and specifications of maritime container supply chain digitalization strategies, developing evaluation criteria, and conducting a case study for proof of concept, the study proposes an operational management process with practical, real-world benefits for port-focal supply chains.

Stochastic MCDM with normal approximation of the uniformly distributed variables for assessing sustainable insulation materials.

The sustainability-related decision-making oftentimes involves uncertain information. One of the key solutions in representing the interval information is the use of the interval information (numbers). This paper proposes a multi-criteria decision-making approach that relies on the algebra of random variables in handling the interval information. The interval information is provided in the form of the uniform distributions that are represented by mean and variance parameters. Following the central limit theorem, the normal approximation is involved. Then, the pair-wise comparisons are facilitated to establish the probabilities of dominance and rank the alternatives accordingly. The proposed approach allows for effectively handling the uncertainty and is user-friendly. The empirical application dealing with selection of the sustainable insulation materials is presented to validate the proposed approach. The technological, economic, environmental, and social facets of sustainability are considered when comparing the insulation materials. Sensitivity of the results is then checked via the Monte Carlo simulation.

Decision optimization techniques for evaluating renewable energy resources for power generation in Ghana: MCDM approach

Renewable energy sources are seen as future energy sources. Ensuring Ghana’s future economic growth requires a balanced energy mix. The study evaluates five renewable energy sources (solar PV, solar thermal, hydro, wind and biomass) against thirteen criteria using multicriteria decision making (MCDM) techniques. Whilst six criteria data were obtained from literature, seven were obtained from experts’ views. Each criterion’s priority weight affects the total ranking of options. CRITIC weighting technique was used to determine the weight of each criterion. MOORA, TOPSIS and COPRAS ranking algorithm were used to rank the five sources. From our analysis, the most promising RE for Ghana is Hydro. The order of prioritization is obtained as hydro > biomass >solar PV > Wind> Solar thermal. The results from the ranking techniques were validated by the Spearman’s correlation co-efficient and p-value to ensure there is positive significant correlation between the ranking techniques. The findings of this study will help in strategic implementation of renewable energy sources for improved sustainability in Ghana.

Analisis Ketahanan (Resilience) Pedagang Kaki Lima di Masa Pandemi Covid-19: Studi Kasus Jalan Sukasari, Kota Bogor, Jawa Barat

Street vendors are one part of SMEs who have experienced the impact of Covid-19, inclusive of street vendors on Jalan Sukasari, Bogor City. The purpose of this study was to determine the most influential factors in recovery and resilience strategies, as well as street vendors in Sukasari street, Bogor City, and alternative recovery strategies for street vendors on Jalan Sukasari, Bogor City. Data collection was conducted by interviews and questionnaire filler by street vendors in Sukasari street. The research analysis used is the Fuzzy-Eckenrode approach analysis as one approach forMulti-Criteria Decision Making. The most influential factors on the resilience of street vendors in Sukasari street, Bogor city after the Covid-19 pandemic based on Fuzzy-Eckenrode analysis are work culture, leadership, and social networks. Alternative strategies based on Fuzzy-TOPSIS analysis are government assistance strategies, digital technology introduction strategies, and debt relief strategies.

A fuzzy multi-criteria decision-making approach for the assessment of forest health applying hyper spectral imageries: A case study from Ramsar forest, North of Iran

The hyperspectral images have so far been widely utilized in monitoring and detecting the changes in a broad range of environmentally related matters. The hyperspectral image analysis yields maps that show spatial dispersion of physical and ecological characteristics of the terrain. Within the scope of the current study, an integrated Fuzzy-MCDM in a Geographic Information Systems (GIS) platform was used to map the health condition of Ramsar forest. Spectral indices can provide different methods for identifying vegetation coverings. For forest health analysis, spectral indices such as NDWI, CRI1, PSRI, PRI, and NDVI were used to infer the causative factors of forest health. The findings highlight the suitability of the used methodology in identifying potential forest statuses, where forest health protection measures can be taken in advance. The results also suggest that the southern and the western aspects of the study area are of “very low” to “low” forest health. Furthermore, the results indicate a high potentiality for applying the spatial MCDM techniques as an effective tool for the forest health investigation.

A Fuzzy Linguistic Multi-Criteria Decision-Making Approach to Assess Emergency Suppliers

Under the influence of COVID-19, various emergency supplies have repeatedly broken links, seriously affecting normal life and hindering the sustainable development of enterprises and society. Therefore, suitable emergency suppliers are crucial. To prioritize and select suitable emergency suppliers, key indicators were determined, and evaluation models were established based on the characteristics of epidemic situations and epidemic prevention materials. The application of the MCDM (multi-criteria decision-making) issue combining fuzzy SWARA (the stepwise weight assessment ratio analysis) and the actor analysis method to emergency supplier selection studies, called the fuzzy SWARA-based actor analysis method, is used to identify appropriate suppliers for optimizing pre-preparation. Results of evaluation system weight computations by the Fuzzy SWARA-based actor analysis method show that the overall prioritization of four non-economic factors in ranking orders are “Delivery Capacity”, “Flexible Supply Capacity”, “Quality”, and “Social Evaluation and Reputation”. For the inclusion of conflicting standards and the unquantifiable feature, economic and non-economic factors were discussed separately and evaluated by language variables. Additionally, the fuzzy actor analysis indicated that economic factors and non-economic factors need to be considered comprehensively for emergency supplier selection. This method has good operability and reference value, convenient for the final choice making according to actual situation.

Fast-Track Product Evaluation From Text Reviews in M-Commerce

The popularity of mobile commerce has offered many new challenges for investigating public sentiments. With an uncountable number of stores and products available on the marketplace, customers heavily relied on the comments or reviews posted by others to support their buying decisions. For the online retailer's side, these text reviews are valuable resources to understand the latest customer expectations and devise a better product plan for launching suitable products to customers. Sentiment analysis is then developed for the evaluation of a significant amount of text data by searching the sentiment words. Nevertheless, different writers may have different perceptions on the sentiment words, and hence, this inconsistency would be amplified. In this connection, a novel approach to obtain public sentiment by combining the topic modeling, fuzzy set, and multi-criteria decision-making approaches is proposed. The uncertainty of different perceptions on the sentiment words is remedied by fuzzy-set.

Two-stage optimal site selection for waste-to-energy plant using single-valued neutrosophic sets and geographic information system based multi-criteria decision-making approach: A case study of Beijing, China

Waste-to-energy (WtE) plant has been attached great importance by more and more countries because of the harmless, energy reducing and recycling characteristics, and has become an important part of the city's normal operation and energy structure. Whereas, the reasonable site selection of the WtE plant is the key to ensure its sustainable development. This paper is designed to provide a two-stage model for the site selection of WtE plants. Firstly, a comprehensive assessment criteria system including environmental, economic, technical and social factors is established by selecting the reasonable influence criterias from the current relevant literature. Considering the fuzziness of the criteria and the bounded knowledge of decision makers, the single-valued neutrosophic sets (SVNSs) are introduced to describe the fuzzy information, andcreatively combined with decision-making and trial evaluation laboratory-analytical network process (DANP) method to determine the influence grades of criterias and calculate the weights. After that, the relevant geographic information layers are collected and the preliminary alternatives are obtained by Geographic information system (GIS) from an overall perspective, then the extend evaluation based on distance from average solution (EDAS) method is utilized to rank the alternatives under the SVNSs environment. Finally, the model is tested to select the optimal alternative for siting the WtE plants in Beijing as an example. It is verified that the model is of great stability and feasibility by sensitivity analysis and comparative analysis. The result shows that this paper can provide a new theoretical basis for the planning of WtE plants.

Development of a site selection methodology for run-of-river hydroelectric power plants within the water-energy-ecosystem nexus

Even though water-energy systems and ecosystems have complex relationships, regional energy policies seldom consider this connection. The current regional energy policies are developed primarily based on technical and socio-economical aspects and lack ecological considerations that may deteriorate the ecosystems and sustainability of these policies. Hence, considering the water-energy-ecosystem nexus in the development stage of the energy policies can aid decision-makers in initiating successful multi-dimensional energy policies. This study proposes a novel approach to develop an environmental index to support the regional energy policies that rely on Run-of-river (RoR) hydroelectric power plants (HEPPs) with a nexus approach. First, significant environmental impacts of RoR HEPPs are identified as environmental flows, impacts on ecologically valuable areas such as heritage sites, wetlands, national parks, river water quality degradation, modification of habitat, and impact on ecosystems and biodiversity loss. Then these impacts are represented through indicators and are aggregated into an overall environmental performance index through a fuzzy multi-criteria decision-making approach. The proposed approach allows the integration of ecological dimensions into the evaluation of RoR HEPPs through easy-to-measure indicators, among which environmental flow is a critical component.

Evaluation and Ranking of E-Government Websites Using Weighted-Combinative Distance-Based Assessment Approach

Electronic government (e-government) now becomes a necessity rather than an option for the countries that aim for improved governance. Indeed, existing agencies of government make a powerful connection with customers through e-government to deliver better, cheaper, and faster services. In the present research, a multi-criteria decision-making (MCDM) approach, namely weighted-combinative distance-based assessment (W-CODAS), is proposed which is a combination of Shannon entropy approach and CODAS and implemented to rank the e-government websites of eight countries by selecting 15 evaluation criteria. Further, the results obtained from W-CODAS method are compared with well-known methods AHP and TOPSIS and validated by Kendall's tau correlation test. The results of the present research based on W-CODAS show that the e-government website of Finland is placed at the top position (Rank 1) followed by UK. Similarly, the Netherlands website occupies last position and is ranked at number eight.