A Novel Hybrid Evaluation Method for Transfer Efficiency Assessment between Rail Transit and Public Bicycles

This paper proposes a new hybrid evaluation method including Improved Analytic Hierarchy Process (IAHP), Entropy Method (EM), and Grey Comprehensive Evaluation Method (GCEM) to assess the transfer efficiency between rail transit and public bicycles. In particular, the IAHP method that replaces the nine-scale approach with three-scale approach to naturally meet the consistency requirements is applied to qualitatively calculate the weights of evaluation indices, the EM method is utilized to calculate the weights of evaluation indices with relatively high degrees of quantification, and the GCEM method is used to calculate the transfer efficiency between rail transit and public bicycles. In addition, a three-level evaluation-index system including target level, criteria level and index level is established. A numerical example is also provided to verify the feasibility of the proposed hybrid evaluation method and explore the reasons for low transfer efficiency between rail transit and public bicycles.</p

Bibliometric analysis of scientific production on methods to aid decision making in the last 40 years

Purpose: Multicriteria methods have gained traction in both academia and industry practices for effective decision-making over the years. This bibliometric study aims to explore and provide an overview of research carried out on multicriteria methods, in its various aspects, over the past forty-four years. Design/Methodology/Approach: The Web of Science (WoS) and Scopus databases were searched for publications from January 1945 to April 29, 2021, on multicriteria methods in titles, abstracts, and keywords. The bibliographic data were analyzed using the R bibliometrix package. Findings: This bibliometric study asserts that 29,050 authors have produced 20,861 documents on the theme of multicriteria methods in 131 countries in the last forty-four years. Scientific production in this area grows at a rate of 13.88 per year. China is the leading country in publications with 14.14%; India with 10.76%; and Iran with 8.09%. Islamic Azad University leads others with 504 publications, followed by the Vilnius Gediminas Technical University with 456 and the National Institute of Technology with 336. As for journals, Expert Systems With Applications; Sustainability; and Journal of Cleaner Production are the leading journals, which account for more than 4.67% of all indexed literature. Furthermore, Zavadskas E. and Wang J have the highest publications in the multicriteria methods domain regarding the authors. Regarding the most commonly used multicriteria decision-making methods, AHP is the most favored approach among the ten countries with the most publications in this research area, followed by TOPSIS, VIKOR, PROMETHEE, and ANP. Practical implications: The bibliometric literature review method allows the researchers to explore the multicriteria research area more extensively than the traditional literature review method. It enables a large dataset of bibliographic records to be systematically analyzed through statistical measures, yielding informative insights. Originality/value: The usefulness of this bibliometric study is summed in presenting an overview of the topic of the multicriteria methods during the previous forty-four years, allowing other academics to use this research as a starting point for their research

Multi-Criteria Decision Matrix Method in the Risk Analysis of Biodiesel Production Processes

Renewable fuel technologies aim to mitigate the non-renewability of fossil fuels, challenges with increased energy demand, and the climate impact of fossil fuel emissions. However, before investing in renewable technologies, there need to be decision strategies that assess and identify the best alternatives according to stakeholder priorities. There is also a concern about whether the technologies that are the “most sustainable” effectively meet the acceptable risk requirements of stakeholders. In response to this question, a risk-adapted multi-criteria decision model was developed and compared to a sustainability study that evaluated five renewable diesel technologies, including Green Diesel I, II, and III; Fischer-Tropsch biodiesel, and the transesterification of biodiesel from vegetable oils. This thesis work provides essential stakeholder perspectives on the risk of these same five technologies and limits the use of probabilistic quantification approaches. Instead, this study uses reasonable assumptions to measure the indicator data objectively. These quantified indicators are considered a cost or benefit and allow adequate comparison of less mature technologies where historical data may be unavailable to more mature ones. This model uses the Analytical Hierarchy Process (AHP) decision strategy with stakeholder survey input to determine criteria and sub-criteria weightings, while the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) subsequently ranks the alternative technologies. The criteria evaluated from a risk perspective include process safety, environmental, economic, technological, and social risks. This risk assessment process has ranked technologies producing alternative fuel types. However, it can also compare and rank bioproduct and process intensification technologies to fossil-derived products and more traditional production techniques. Moreover, the central conclusion of this work is that an even more comprehensive tool is needed that combines risk and sustainability aspects. This conclusion is due to the sustainability study indicating Fischer-Tropsch diesel as the best option. At the same time, the present risk research revealed it as the option with the most significant comparative risk

An Investigation into Factors Affecting the Chilled Food Industry

With the advent of Industry 4.0, many new approaches towards process monitoring, benchmarking and traceability are becoming available, and these techniques have the potential to radically transform the agri-food sector. In particular, the chilled food supply chain (CFSC) contains a number of unique challenges by virtue of it being thought of as a temperature controlled supply chain. Therefore, once the key issues affecting the CFSC have been identified, algorithms can be proposed, which would allow realistic thresholds to be established for managing these problems on the micro, meso and macro scales. Hence, a study is required into factors affecting the CFSC within the scope of Industry 4.0. The study itself has been broken down into four main topics: identifying the key issues within the CFSC; implementing a philosophy of continuous improvement within the CFSC; identifying uncertainty within the CFSC; improving and measuring the performance of the supply chain. However, as a consequence of this study two further topics were added: a discussion of some of the issues surrounding information sharing between retailers and suppliers; some of the wider issues affecting food losses and wastage (FLW) on the micro, meso and macro scales. A hybrid algorithm is developed, which incorporates the analytic hierarchical process (AHP) for qualitative issues and data envelopment analysis (DEA) for quantitative issues. The hybrid algorithm itself is a development of the internal auditing algorithm proposed by Sueyoshi et al (2009), which in turn was developed following corporate scandals such as Tyco, Enron, and WorldCom, which have led to a decline in public trust. However, the advantage of the proposed solution is that all of the key issues within the CFSC identified can be managed from a single computer terminal, whilst the risk of food contamination such as the 2013 horsemeat scandal can be avoided via improved traceability

Multi-criteria decision making support tools for maintenance of marine machinery systems

PhD ThesisFor ship systems to remain reliable and safe they must be effectively maintained through a sound maintenance management system. The three major elements of maintenance management systems are; risk assessment, maintenance strategy selection and maintenance task interval determination. The implementation of these elements will generally determine the level of ship system safety and reliability. Reliability Centred Maintenance (RCM) is one method that can be used to optimise maintenance management systems. However the tools used within the framework of the RCM methodology have limitations which may compromise the efficiency of RCM in achieving the desired results. This research presents the development of tools to support the RCM methodology and improve its effectiveness in marine maintenance system applications. Each of the three elements of the maintenance management system has been considered in turn. With regard to risk assessment, two Multi-Criteria Decision Making techniques (MCDM); Vlsekriterijumska Optimizacija Ikompromisno Resenje, meaning: Multi-criteria Optimization and Compromise Solution (VIKOR) and Compromise Programming (CP) have been integrated into Failure Mode and Effects Analysis (FMEA) along with a novel averaging technique which allows the use of incomplete or imprecise failure data. Three hybrid MCDM techniques have then been compared for maintenance strategy selection; an integrated Delphi-Analytical Hierarchy Process (AHP) methodology, an integrated Delphi-AHP-PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluation) methodology and an integrated Delphi-AHP-TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methodology. Maintenance task interval determination has been implemented using a MCDM framework integrating a delay time model to determine the optimum inspection interval and using the age replacement model for the scheduled replacement tasks. A case study based on a marine Diesel engine has been developed with input from experts in the field to demonstrate the effectiveness of the proposed methodologies.Tertiary Education Trust Fund (TETFUND), a scholarship body of the Federal Republic of Nigeria for providing the fund for this research. My gratitude also goes to Federal University of Petroleum Resource, Effurun, Nigeria for giving me the opportunity to be a beneficiary of the scholarship

Integrated Frameworks for Effective Multi-criteria Decision Making in Reliability Centred Maintenance of Industrial Machines

No abstract availabl

Environmental impact of the effluents discharging from full-scale wastewater treatment plants evaluated by a hybrid fuzzy approach

Increasing attention is being paid to the environmental impacts of wastewater treatment plant (WWTP) effluent. In this study, comprehensive environmental impact analyses (EIAs) were performed for the secondary treatment processes, tertiary treatment processes, and entire plants at five full-scale WWTPs in Kunming, China. The EIAs took into account greenhouse gas (GHG) emissions, potential for the effluent to cause eutrophication, ecological risks posed by endocrine disrupting compounds (EDCs) in treated effluent, and the risks posed by heavy metals in excess sludge. A comprehensive assessment toward environmental sustainability was performed using a fuzzy approach. The results indicated that the biological treatment process made the largest contribution (>68% of the total) of the secondary treatment processes to GHG emissions and that electricity consumption made the largest contribution (>64% of the total) of the tertiary treatment processes to GHG emissions. Large numbers of EDCs were removed during the secondary treatment processes, but the potential ecological risks posed by EDCs still require attention. High mercury concentrations were found in excess sludge. The plant that removed the largest proportion of pollutants and produced effluent posing the least ecological risks gave the best comprehensive EIA performance

A Fuzzy Data Envelopment Analysis Framework for Dealing with Uncertainty Impacts of Input–Output Life Cycle Assessment Models on Eco-efficiency Assessment

The uncertainty in the results of input–output-based life cycle assessment models makes the sustainability performance assessment and ranking a challenging task. Therefore, introducing a new approach, fuzzy data envelopment analysis, is critical; since such a method could make it possible to integrate the uncertainty in the results of the life cycle assessment models into the decision-making for sustainability benchmarking and ranking. In this paper, a fuzzy data envelopment analysis model was coupled with an input–output-based life cycle assessment approach to perform the sustainability performance assessment of the 33 food manufacturing sectors in the United States. Seven environmental impact categories were considered the inputs and the total production amounts were identified as the output category, where each food manufacturing sector was considered a decision-making unit. To apply the proposed approach, the life cycle assessment results were formulated as fuzzy crisp valued-intervals and integrated with fuzzy data envelopment analysis model, thus, sustainability performance indices were quantified. Results indicated that majority (31 out of 33) of the food manufacturing sectors were not found to be efficient, where the overall sustainability performance scores ranged between 0.21 and 1.00 (efficient), and the average sustainability performance was found to be 0.66. To validate the current study\u27s findings, a comparative analysis with the results of a previous work was also performed. The major contribution of the proposed framework is that the effects of uncertainty associated with input–output-based life cycle assessment approaches can be successfully tackled with the proposed Fuzzy DEA framework which can have a great area of application in research and business organizations that use with eco-efficiency as a sustainability performance metric