Analysis of industry 4.0 implementation in mobility sector: An integrated approach based on QFD, BWM, and stratified combined compromise solution under fuzzy environment

The role of new technologies in industrial and service sector is inevitable. Various sectors like transport / mobility have decided to remodel and redesign their infrastructures by implementing innovative devices and strategies. Transport / mobility sector is one of the most fast-growing industries which demands innovative solutions, however, it will be complex to derive optimal decision while one confront uncertain conditions and variables. In this paper, we develop a decision support system for technology adoption in transport / mobility division within the context of Industry 4.0 considering a case study in Spain. To find the adopted technology in this sector, several alternatives (options) and variables (criteria) should be assumed. We propose an integrated decision-making system including quality function deployment (QFD) and best-worst method (BWM) to find the importance weight of each criterion. After we apply the stratified Combined compromise solution (S-CoCoSo) to rate the alternatives and rank them under a multi-scenario perspective. The results will be analyzed through some sensitivity analysis actions. The novelty of our proposed decision support model contributes to the mobility sector and releases guidelines to managers and policy makers

Evaluation of information and communication technology development in G7 countries: an integrated MCDM approach

Information and communication technology (ICT) contributes highly to various sectors of modern societies. Due to rapid growth of ICT and its spread into different sectors, ICT now has noticeable impacts on economic and social growth. Considering both positive and negative impacts, governments are continuously working on proposing better policies and recommendations to improve their ICT infrastructures. However, proposing better policies is highly depended on understanding past and current policies to have a complete overview of the situation. In this regard, evaluation of countries’ performance in terms of ICT development is of great significance. This paper attempts to evaluate the ICT development based on social and economic indicators using an integrated MCDM approach. To provide a real-life benchmark, G7 countries as major developed countries are investigated using real data from OECD datasets. For this purpose, six major indicators as ICT employment, ICT goods exports, ICT investment, ICT value-added, and internet access are considered to comparatively evaluate performance of G7 countries. Results indicate that United States of America along with Japan as top countries based on their ICT development while countries such as Italy and Canada are found to have the weakest performance which should upgrade their ICT policies to maximize their performance

Reformulations of a bi-level optimization problem detecting collusions in deregulated electricity markets

Main goal of deregulated electricity markets is to provide an environment with perfect competition among generation companies. Tacit collusion is considered as one of the main threats that may disrupt the competition in electricity markets operated by an independent system operator and increase the electricity price. In order to detect collusion opportunities in the market, we present reformulations for a gametheoretic bi-level optimization problem (Aliabadi et al. 2016). There exists no commercial solvers to directly solve a bi-level problem. First, we improve the existing equivalent reformulations of the problem (Çelebi et al. 2019). Then, we propose two new reformulations based on Karush–Kuhn–Tucker (KKT) conditions together with Active Set Theory, and Special Ordered Set (SOS) variables. Four groups of test instances with varying size are used to show and compare the efficiency and effectiveness of the reformulations in detecting collusive opportunitie

A hybrid genetic algorithm for appointment scheduling in a health examination system

A health examination system is a large system comprised of many units that include sectors or rooms, such as healthcare clinics, each of which requires unique tasks and experts to offer complete and timely healthcare. In general, every HES must accommodate a diverse population of individuals with unique medical histories and special behaviours. Access to and consideration of individuals' medical histories can reduce total exam times within a HES. Therefore, this study proposed a hybrid genetic algorithm that can be used to address the appointment scheduling in a HES to reduce the total preparation time of each room or sector, with a general aim to reduce total examination time. The proposed method is performed for 18 cases with different patient and room sizes in a health system. Results obtained all these cases showed higher accuracy and performance of the proposed method to the CPLEX solver in terms of the objective function and computational time

Charging type selection for electric buses using interval-valued neutrosophic decision support model

Using electricity to fuel buses has always been known as a green option for the public bus operations considering the recent regulations on environmental and climate concerns. Emission-free public transportation modes such as electric buses improve local air quality and reduce noise pollution and also contribute to achieving sustainability goals by developing a sustainable transportation system. Many projects have been carried out using different charging strategies for electric buses around the world. However, selecting the most appropriate charging strategy for the electric buses in the public transportation is a challenging and multidimensional decision-making problem for transportation management sector. Therefore, this article proposes a decision support model based on the interval-valued neutrosophic set which uses Shannon's entropy and mixed aggregation by comprehensive normalization technique to choose the most appropriate charging type for urban electric buses among alternatives such as opportunity, depot, inductive, and no shift. This article presents a real-life case study in Turkey to illustrate the applicability and advantages of the proposed model. Extensive sensitivity analysis and comparative analysis tests are conducted to show the robustness of the proposed methodology. The results show that depot charging is the most suitable charging strategy for Istanbul's bus operator system

Analyzing failures in adoption of smart technologies for medical waste management systems: a type-2 neutrosophic-based approach

Medical waste management (MWM) systems are considered among the most important urban systems nowadays. Cities in different countries prefer to transform their infrastructure based on sustainability guidelines and practices. Meanwhile, smart technologies such as Internet of Things (IoT) and blockchain are being recently used in different urban systems of cities that aim to transform into smart cities. MWM systems are one of the main targets of integrating such smart technologies to maximize economic and social profits and minimize environmental issues. However, the transformation of traditional MWM systems into smart MWM systems and the adoption of such technologies can be a very resource-consuming task. One of the possible tasks in this process can be the identification of factors that cause failure in the adoption of smart technologies. Therefore, this study proposes a multi-criteria evaluation model based on type-2 neutrosophic numbers (T2NNs) to identify factors contributing to failure in the adoption of IoT and blockchain in smart MWM systems in Istanbul, Turkey. Results of the case study indicate that training for different stakeholders, market acceptance, transparency, and professional personnel are the main factors that lead to failure in the adoption of smart technologies. Training for different stakeholders, market acceptance, transparency, and professional personnel factors obtained distance values of 0.494, 0.381, 0.375, and 0.278, respectively, against the best factor which is security and privacy. In order to validate the results of the proposed approach, a sensitivity analysis test is performed. Results of this study can be useful for governmental and private MWM and green companies that are planning to adopt IoT and blockchain within their waste management (WM) system

A mulTi-noRmalization mUlti-distance aSsessmenT (TRUST) approach for locating a battery swapping station for electric scooters

Due to high popularity of electric scooters, cities with high population have faced challenges regarding establishment of battery swapping stations (BSS) along populated areas of the urban districts. However, locating a BSS in a big city is a multi-dimensional problem which require reliable tools to efficiently address. This paper proposes a novel robust decision-making tool, named mulTi-noRmalization mUlti-distance aSsessmenT (TRUST), to tackle location selection problem for BSS considering sustainability criteria. The proposed approach applies a multi-normalization procedure using three linear normalization techniques, logarithmic-normalization, and constraint-based normalization which are integrated through an aggregation operator. Then, Euclidean, Manhattan, Lorentzian, and Pearson distance measures are used to determine distance of alternatives from the negative ideal solution in order to calculate the final score. Advantages of the proposed approach are consideration of a multi-normalization algorithm to minimize subjectivity in normalized data, consideration of constraint-based normalization technique to ensure specific standards, and utilization of four distance measures through a two-stage process to determine a relative distance score. To show the feasibility and applicability of the new approach, a real-life case study is investigated to locate a BSS in Istanbul. Results show that the best alternative is Beyoğlu for locating a BSS for electric scooters

A comparative assessment of air quality across European countries using an integrated decision support model

Funding Information: The European Union (EU) has been active in creating a cleaner society by controlling air pollutants within different sectors such as transportation [13] and industrial activities [14]. Air pollution control in the EU and tracking of emission commitments of its member states is administered by the European Environment Agency [15], supporting policies aiming at enhancing green economics, sustainable industries, high environmental development, sustainable and smart societies, and cleaner agricultural activities [16]. Publisher Copyright: © 2021 Elsevier LtdReducing air pollution including greenhouse gas emissions originating from extensive use of fossil fuels is critical for European countries aiming at improving their environment and at carbon neutrality by the middle of this century. To optimally reduce the air pollutants and mitigate the climate change, not only national or European Union level regulation need to be considered, but also international agreements such as the Sustainable Development Goals, Kyoto Protocol, and Paris Climate Agreement need to be included in these strategies. Managing such a complex framework would benefit from reliable multi-criteria decision-making approaches. Current models to enhance air quality often concentrate on one criterion at a time and focus on momentary improvements only, unable to offer longstanding enhancement. Therefore, comparative analysis of emissions of several air pollutants simultaneously is highly relevant empowering decision-makers with better tools for policy development. The focus of this study is on a decision support model based on the Best-Worst Method and the Measurement of Alternatives and Ranking According to Compromise Solution method to comparatively analyze air pollutants of 22 European countries. This study is the first in its kind to develop an integrated decision model for air quality assessment considering six air pollutants. Extensive sensitivity analyses were performed to highlight the impacts from different scenarios on the decision-making. The results indicate that Sweden, Latvia, France, Lithuania, Hungary, and Italy ranked as the top six countries with the lowest emission. However, Finland, Poland, the Czech Republic, Luxembourg, and Estonia had the lowest overall ranking and the highest per capita emissions. The proposed methodology and evaluation framework can provide a helpful tool for developing regional and national strategies to minimize air pollutants and to improve environmental sustainability.Peer reviewe

Developing benders decomposition algorithm for a green supply chain network of mine industry: Case of Iranian mine industry

This paper attempts to design a three-echelon supply chain network for mine industry considering suppliers, manufacturing centers and distributors with different kinds of vehicles. A multi-objective mixed integer programming model is proposed to minimize transportation costs, shortage costs, purchase costs, production costs and CO2 emissions of vehicles with fuzzy demand values. ε-constraint method is used in order to convert multiple objective functions to a single objective function. Benders decomposition algorithm is applied to solve the model under three demand-based scenarios. A case study is done on Iranian mine industry to present the significance and applicability of the proposed model in a real-life case problem as well as the efficiency of Benders decomposition. Keywords: Supply chain management, Benders decomposition, Iranian mine industry, ε-constraint metho