A hybrid decomposed fuzzy multi-criteria decision-making model for optimizing parcel lockers location in the last-mile delivery landscape

Applied Soft Computing, Год журнала: 2024, Номер 154, С. 111321 - 111321

Опубликована: Фев. 6, 2024

Parcel lockers are considered an effective solution to address inefficiencies in last mile delivery. However, choosing the appropriate location is crucial provide optimal service and improve logistic performance. Therefore, this research aims assess most suitable locations for parcel Dublin, capital of Ireland, using a novel hybrid decision-making model. This study seeks extend Combinative Distance based Assessment method integrate Analytical Hierarchy Process handle locker evaluation problems through Decomposed Fuzzy Sets. The proposed model pioneering application real-life scenarios, contributing existing knowledge field. integrated we propose offers approach selecting locations. outcomes will valuable insights policymakers, aiding them making strategic decisions regarding selection within Dublin city.

Язык: Английский

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ADCT-Net: Adaptive traffic forecasting neural network via dual-graphic cross-fused transformer

Information Fusion, Год журнала: 2023, Номер 103, С. 102122 - 102122

Опубликована: Ноя. 4, 2023

Язык: Английский

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Projection based regret theory on three-way decision model in probabilistic interval-valued q-rung orthopair hesitant fuzzy set and its application to medicine company

Artificial Intelligence Review, Год журнала: 2023, Номер 56(S3), С. 3617 - 3649

Опубликована: Ноя. 5, 2023

Язык: Английский

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A novel spherical decision-making model for measuring the separateness of preferences for drivers’ behavior factors associated with road traffic accidents

Expert Systems with Applications, Год журнала: 2023, Номер 238, С. 122318 - 122318

Опубликована: Окт. 27, 2023

Enhancing road safety through a more effective understanding of drivers' behavior is viable approach to curbing traffic collisions. When evaluating driving behavior, the selection methodologies diverse, often facing scrutiny. This study aims detect, compare and quantify critical factors concerning in Budapest, Hungary. Employing Analytic Hierarchy Process (AHP) within spherical fuzzy framework, based on Spherical Fuzzy Sets (SFS), we assess driver preferences. Kendall's test gauges' agreement levels among hierarchical groups. At Level 1, our AHP (SFAHP) identifies 'Lapses' as crucial, followed by 'Errors' for experienced young drivers. However, foreign drivers prioritize 'Violations.' 2, "Aggressive violations" prevails across all groups, contrasting with "Ordinary violations." 3, "Driving alcohol use" reigns supreme. concordance demonstrates low similarity at while strong surfaces Levels 2 3. Our insights can empower transportation authorities bolster strategies addressing these pivotal factors.

Язык: Английский

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Fuzzy decision-making framework for explainable golden multi-machine learning models for real-time adversarial attack detection in Vehicular Ad-hoc Networks

Information Fusion, Год журнала: 2023, Номер 105, С. 102208 - 102208

Опубликована: Дек. 27, 2023

This paper addresses various issues in the literature concerning adversarial attack detection Vehicular Ad-hoc Networks (VANETs). These include failure to consider both normal and perspectives simultaneously Machine Learning (ML) model development, lack of diversity preprocessing techniques for VANETs communication datasets, inadequate selection guidelines real-time models, limited emphasis on explainability detection. In this study, we propose an original fuzzy decision-making framework that incorporates multiple fusion standpoints. Our aims evaluate multi-ML models VANETs, focusing three stages. The first stage involves identifying Dedicated Short-Range Communication (DSRC) data using standard approaches. Two scenarios, jammed, are considered, resulting two DSRC datasets. second stage, develop based datasets feature dataset-1 dataset-2, respectively. third evaluates a approach Fuzzy Decision by Opinion Score Method (FDOSM) decision matrix. External Fusion (EFD) settings FDOSM address individual ranking variance, provide unique rank select best model. Experimental results demonstrate K-Nearest Neighbors Algorithm (kNN) achieves highest explain score 0.2048 preprocessing, while Random Forest (RF) applied dataset-2 emerges as most robust golden against attacks, with 0.1819. finding suggests Principal Component Analysis (PCA) is more suitable addressing perspectives. Furthermore, our undergoes evaluation terms systematic rank, sensitivity analysis, comparison analysis. Overall, provides valuable insights researchers practitioners informing execution, selection, interpretation tackle problems effectively. new demonstrates effective.

Язык: Английский

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Selection of electric bus models using 2-tuple linguistic T-spherical fuzzy-based decision-making model

Expert Systems with Applications, Год журнала: 2024, Номер 249, С. 123498 - 123498

Опубликована: Фев. 19, 2024

Due to energy's global reliance on fossil fuels and population growth, GHG emissions their repercussions have attracted attention. cheaper cost cleaner environment, renewable energy modes of transportation like electric vehicles are highly sought after. Electric beneficial, but they also emit indirectly in power plants that generate electricity, which could affect small medium communities. Thus, it is crucial assess such transportation's performance while considering key aspects criteria. However, scholarly works this field not fully addressed the deployment a comprehensive vehicle decision-making support system. This study addresses bus selection by introducing novel approach Multi-Criteria Decision-Making (MCDM) utilizing developed integrated fuzzy set. We introduce an combines Entropy weighting with 2-tuple Linguistic T-Spherical Fuzzy Decision Opinion Score Method (2TLTS-FDOSM). designed tackle challenges associated evaluating feasibility models (EBMs) addressing theoretical challenge MCDM context presented case study. These include dealing ambiguities inconsistencies among decision-makers. The former method utilized ascertain significance assessment criteria, whereas latter applied select most favorable EBM weights obtained. As for 2TLTS-FDOSM results, out all (n=6) EBMs considered, A3 (11-E) obtained highest score value, (9-E) had lowest score. robustness results confirmed through sensitivity analysis.

Язык: Английский

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Evaluation of food waste treatment techniques using the complex q-rung orthopair fuzzy generalized TODIM method with weighted power geometric operator

Journal of Environmental Management, Год журнала: 2024, Номер 353, С. 120105 - 120105

Опубликована: Фев. 1, 2024

Food waste has received wide attention due to its hazardous environmental effects, such as soil, water, and air pollution. Evaluating food treatment techniques is imperative realize sustainability. This study proposes an integrated framework, the complex q-rung orthopair fuzzy-generalized TODIM (an acronym in Portuguese for interactive multi-criteria decision-making) method with weighted power geometric operator, assess appropriate technique waste. The assessment of can be divided into three phases: information processing, fusion, ranking alternatives. Firstly, fuzzy set flexibly describes periodic characteristics processing process various parameters q. Then, operator employed calculate weight expert form group evaluation matrix, which each input rating depends upon other ratings. It simulate mutual support, multiplicative preferences, interrelationship experts. Next, generalized rank techniques, considering experts’ psychological bounded behavior. Subsequently, a real-world application case examines practicability proposed framework. Furthermore, sensitivity analysis verifies validity stability presented comparative highlights effectiveness this framework using existing frameworks. According result, Anaerobic digestion (0.0043) highest priority among considered alternatives, while Incineration (−0.0009) lowest.

Язык: Английский

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An extension of the best–worst method based on the spherical fuzzy sets for multi-criteria decision-making

Granular Computing, Год журнала: 2024, Номер 9(2)

Опубликована: Март 30, 2024

Abstract The ambiguous information in multi-criteria decision-making (MCDM) and the vagueness of decision-makers for qualitative judgments necessitate accurate tools to overcome uncertainties generate reliable solutions. As one latest most powerful MCDM methods obtaining criteria weight, best–worst method (BWM) has been developed. Compared other methods, such as analytic hierarchy process, BWM requires fewer pairwise comparisons produces more consistent results. Consequently, main objective this study is develop an extension using spherical fuzzy sets (SFS) address problems under uncertain conditions. Hesitancy, non-membership, membership degrees are three-dimensional functions included SFS. presence three defined allows express their accurately. An optimization model based on nonlinear constraints used determine optimal weight coefficients (SF-BWM). Additionally, a consistency ratio proposed SF-BWM assess reliability comparison versions BWM. examined two numerical problems. results show that provided weights with same priority However, there differences values indicate accuracy obtained advantage providing better ratio. Based comparative analysis, threefold than which leads

Язык: Английский

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An integrated picture fuzzy standard deviation and pivot pairwise assessment method for assessing the drivers of digital transformation in higher education institutions

Engineering Applications of Artificial Intelligence, Год журнала: 2024, Номер 133, С. 108508 - 108508

Опубликована: Май 14, 2024

Язык: Английский

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Assessment of bio-medical waste disposal techniques using interval-valued q-rung orthopair fuzzy soft set based EDAS method

Artificial Intelligence Review, Год журнала: 2024, Номер 57(8)

Опубликована: Июль 16, 2024

Abstract Selecting an optimum technique for disposing of biomedical waste is a frequently observed obstacle in multi-attribute group decision-making (MAGDM) problems. The MAGDM commonly applied to tackle states originated by obscurity and vagueness. interval-valued q-rung orthopair fuzzy soft set novel variant sets. main objective this study introduce the Einstein-ordered weighted Einstein hybrid aggregation operators. Based on developed operators, approach, Evaluation based Distance from Average Solution introduced solve problem. execution proposed approach demonstrates significant impact determining most effective strategy handle waste. Our approach's practicality confirmed case focusing selecting Biomedical Waste (BMW) treatment. This shows that autoclaving method disposal BMW. Comparative sensitivity analysis confirms consistency effectiveness our methodology. comparative indicates effects are more feasible realistic than prevailing techniques.

Язык: Английский

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