Algorithms for probabilistic uncertain linguistic multiple attribute group decision making based on the GRA and CRITIC method: application to location planning of electric vehicle charging stations

Electric vehicles (EVs) could be regarded as one of the most innovative and high technologies all over the world to cope with the fossil fuel energy resource crisis and environmental pollution issues. As the initiatory task of EV charging station (EVCS) construction, site selection play an important part throughout the whole life cycle, which is deemed to be multiple attribute group decision making (MAGDM) problem involving many experts and many conflicting attributes. In this paper, a grey relational analysis (GRA) method is investigated to tackle the probabilistic uncertain linguistic MAGDM in which the attribute weights are completely unknown information. Firstly, the definition of the expected value is then employed to objectively derive the attribute weights based on the CRiteria Importance Through Intercriteria Correlation (CRITIC) method. Then, the optimal alternative is chosen by calculating largest relative relational degree from the probabilistic uncertain linguistic positive ideal solution (PULPIS) which considers both the largest grey relational coefficient from the PULPIS and the smallest grey relational coefficient from the probabilistic uncertain linguistic negative ideal solution (PULNIS). Finally, a numerical case for site selection of electric vehicle charging stations (EVCS) is designed to illustrate the proposed method. The result shows the approach is simple, effective and easy to calculate

Sustainability in Industry, Innovation and Infrastructure: A MCDM Based Performance Evaluation of European Union and Türkiye for Sustainable Development Goal 9 (SDG 9)

Purpose: The aim of this study is to perform two distinct cross-country evaluations including European Union (EU) countries and Türkiye, focusing on Sustainable Development Goal 9 (SDG 9): Industry, innovation and infrastructure. The study aims to obtain rankings that display the relative standings of countries and identify areas for potential enhancement. Methodology: An integrated objective criteria weighting, VIKOR, and MAIRCA based Multi-Criteria Decision Making (MCDM) approach has been employed. Findings: Based on the first analysis, high speed internet coverage (HSI) and the share of rail and inland waterways in inland freight transport (SRI) were prominent criteria, and in the MCDM analysis, Sweden displayed the highest performance, while Greece and Croatia showed the lowest performance. In the second analysis, which included Türkiye, tertiary educational attainment (TEA) criteria stood out; while, Sweden maintained its leading position. Türkiye initially had poor performance in the early years but later improved, reaching a mid-level position among 26 countries by 2020. However, a significant decline in performance was observed in the last two years. In addition, during the handled period Türkiye witnessed a decline in both the number of patent applications and the share of buses and trains in inland passenger transport. Thereby, novel policies and incentives could be formulated to overcome these issues. Originality: Two distinct cross-country analyses were conducted in accordance with the SDG 9 by adopting the most recent data and an integrated methodology. Within this context, EU countries were compared both among themselves and with Türkiye, and valuable findings were presented

Multi-Stage Multi-Criteria Decision Analysis for Siting Electric Vehicle Charging Stations within and across Border Regions

Electric Vehicles (EVs) replace fossil fuel vehicles in effort towards having more sustainable transport systems. The battery of an EV is recharged at a charging point using electricity. While some recharging will be required at locations where vehicles are normally parked, other recharging could be necessary at strategic locations of vehicular travel. Certain locations are suitable for EV charging station deployment, others are not. A multi-stage decision analysis methodology for selecting suitable locations for installing EV charging station is presented. The multi-stage approach makes it possible to select critical criteria with respect to any defined objectives of the EV charging station and techno-physio-socio-economic factors without which the EV charging station could not be deployed or would not serve its designated purpose. In a case, the type of charging station is specified, and a purpose is defined: rapid EV charging stations intended for public use within and across border regions. Applied in siting real EV charging stations at optimal locations, stages in the methodology present additional techno-physio-socio-economic factors in deploying the type of EV charging stations at optimal locations and keep the EV charging stations operating within acceptable standards. Some locations were dropped at the critical analysis stage; others were dropped at the site-specific analysis stage and replacement sites were required in certain instances. Final locations included most optimal, less optimal, least optimal, and strategic or special need locations. The average distances between contiguous recharging locations were less than 60 miles. Using any specified separation standard, the number of additional EV charging stations required between EV charging stations were determinable with the Pool Box. The Overall Charging Station Availability quadrants suggest that the overall user experience could get worse as less-standardized additional EV charging stations are deployed

A novel stochastic fuzzy decision model for agile and sustainable global manufacturing outsourcing partner selection in footwear industry

Purpose – The decision-making to outsource and select the most suitable global manufacturing outsourcing partner (MOP) is complex and uncertain due to multiple conflicting qualitative and quantitative criteria as well as multiple alternatives. Vagueness and variability exist in ratings of criteria and alternatives by group of decision-makers (DMs). The paper provides a novel Stochastic Fuzzy (SF) method for evaluation and selection of agile and sustainable global MOP in uncertain and volatile business environment. Design/methodology/approach – Four main selection criteria for global MOP selection were identified such as economic, agile, environmental and social criteria. Total 16 sub-criteria were selected. To consider the vagueness and variability in ratings by group of DMs, SF method using t-distribution or z-distribution was adopted. The criteria weights were determined using the Stochastic Fuzzy-CRiteria Importance Through Intercriteria Correlation (SF-CRITIC), while MOP selection was carried out using Stochastic FuzzyVIseKriterijumskaOptimizacija I KompromisnoResenje (SF-VIKOR) in the case study of footwear industry. Sensitivity analysis was performed to test the robustness of the proposed model. A comparative analysis of SFVIKOR and VIKOR was made. Findings – The worker’s wages and welfare, product price, product quality, green manufacturing process and collaboration with partners are the most important criteria for MOP selection. The MOP3 was found to be the best agile and sustainable global MOP for the footwear company. In sensitivity analysis, significance level is found to have important role in MOP ranking. Hence, the study concluded that integrated SF-CRITIC and SF-VIKOR is an improved method for MOP selection problem. Research limitations/implications – In a group decision making, ambiguity, impreciseness and variability are found in relative ratings. Fuzzy variant Multi-Criteria Decision-Making methods cover impreciseness in ratings but not the variability. On the other hand, deterministic models do not cover either. Hence, the stochastic method based on the probability theory combining fuzzy theory is proposed to deal with decision-making problems in imprecise and uncertain environments. Most notably, the proposed model has novelty as it captures and reveals both the stochastic perspective and the fuzziness perspective in rating by group of DMs. Practical implications – The proposed multi-criteria group decision-making model contributes to the sustainable and agile footwear supply chain management and will help the policymakers in selecting the best global MOP. Originality/value – To the best of the authors’ knowledge, SF method has not been used to select MOP in the existing literature. For the first time, integrated SF-CRITIC and SF-VIKOR method were applied to select the best agile and sustainable MOP under uncertainty. Unlike other studies, this study considered agile criteria along with triple bottom line sustainable criteria for MOP selection. The novel method of SF assessment contributes to the literature and put forward the managerial implication for improving agility and sustainability of global manufacturing outsourcing in footwear industry

A spatial decision support system for the analysis of environmental impacts of integrated crop-livestock production system

Recent shifts toward intensive and large confined livestock production units to enhance economic growth coupled with increased concerns for air, soil, and water quality have necessitated the development of computer-based management decision support systems for selecting environmentally sound production sites and for planning sustainable production systems. This dissertation describes the development and application of an interactive spatial decision support system that integrates a geographic information system, spatial and biophysical modeling, and a knowledge-based system into an interactive tool to facilitate planning and management of environmentally-sound livestock production. The spatial decision support can be used to select suitable watershed land areas for siting livestock production, to select fields for manure application, and to determine the potential impacts of livestock production practices on ground and surface water quality. The site selection component of the spatial decision support system is based on the ARC/INFO geographic information system and incorporates the effects of land use, soil type, topography, proximity to roads and surface water bodies, and other aesthetic and political considerations as well as multicriteria analysis techniques. The groundwater quality modeling component of the decision support system integrates a geographic information system and water quality modeling, using training sets from NLEAP water quality modeling, to estimate nitrate leaching. In order to evaluate nutrient loading on surface water from integrated crop-livestock production a surface water quality model capable of incorporating the spatial dynamics of watershed was needed. The AGNPS distributed-parameter model was used for this purpose. The AGNPS model integrated with ARC/INFO GIS forms a user-friendly modeling interface for surface water quality analysis. The interface automates extraction of the input parameters from GIS data layers and allows the user to interactively generate scenarios of nutrient management practices in crop-livestock production. In order to demonstrate utility of the integrated system, example applications were performed on 7075-ha Lake Icaria watershed in southern Iowa

Wasserstein distance-based probabilistic linguistic TODIM method with application to the evaluation of sustainable rural tourism potential

The evaluation of sustainable rural tourism potential is a key work in sustainable rural tourism development. Due to the complexity of the rural tourism development situation and the limited cognition of people, most of the assessment problems for sustainable rural tourism potential are highly uncertain, which brings challenges to the characterisation and measurement of evaluation information. Besides, decision-makers (DMs) usually do not exhibit complete rationality in the practical evaluation process. To tackle such problems, this paper proposes a new behaviour multi-attribute group decision-making (MAGDM) method with probabilistic linguistic terms sets (PLTSs) by integrating Wasserstein distance measure into TODIM (an acronym in Portuguese of interactive and multicriteria decision making) method. Firstly, a new Wasserstein-based distance measure with PLTSs is defined, and some properties of the proposed distance are developed. Secondly, based on the correlation coefficient among attributes and standard deviation of each attribute, an attribute weight determination method (called PL-CRITIC method) is proposed. Subsequently, a Wasserstein distance-based probabilistic linguistic TODIM method is developed. Finally, the proposed method is applied to the evaluation of sustainable rural tourism potential, along with sensitivity and comparative analyses, as a means of illustrating the effectiveness and advantages of the new method