Development, test and comparison of two Multiple Criteria Decision Analysis(MCDA) models: A case of healthcare infrastructure location

When planning a new development, location decisions have always been a major issue. This paper examines and compares two modelling methods used to inform a healthcare infrastructure location decision. Two Multiple Criteria Decision Analysis (MCDA) models were developed to support the optimisation of this decision-making process, within a National Health Service (NHS) organisation, in the UK. The proposed model structure is based on seven criteria (environment and safety, size, total cost, accessibility, design, risks and population profile) and 28 sub-criteria. First, Evidential Reasoning (ER) was used to solve the model, then, the processes and results were compared with the Analytical Hierarchy Process (AHP). It was established that using ER or AHP led to the same solutions. However, the scores between the alternatives were significantly different; which impacted the stakeholders‟ decision-making. As the processes differ according to the model selected, ER or AHP, it is relevant to establish the practical and managerial implications for selecting one model or the other and providing evidence of which models best fit this specific environment. To achieve an optimum operational decision it is argued, in this study, that the most transparent and robust framework is achieved by merging ER process with the pair-wise comparison, an element of AHP. This paper makes a defined contribution by developing and examining the use of MCDA models, to rationalise new healthcare infrastructure location, with the proposed model to be used for future decision. Moreover, very few studies comparing different MCDA techniques were found, this study results enable practitioners to consider even further the modelling characteristics to ensure the development of a reliable framework, even if this means applying a hybrid approach

A Methodology for the Selection of Multi-Criteria Decision Analysis Methods in Real Estate and Land Management Processes

Real estate and land management are characterised by a complex, elaborate combination of technical, regulatory and governmental factors. In Europe, Public Administrators must address the complex decision-making problems that need to be resolved, while also acting in consideration of the expectations of the different stakeholders involved in settlement transformation. In complex situations (e.g., with different aspects to be considered and multilevel actors involved), decision-making processes are often used to solve multidisciplinary and multidimensional analyses, which support the choices of those who are making the decision. Multi-Criteria Decision Analysis (MCDA) methods are included among the examination and evaluation techniques considered useful by the European Community. Such analyses and techniques are performed using methods, which aim to reach a synthesis of the various forms of input data needed to define decision-making problems of a similar complexity. Thus, one or more of the conclusions reached allow for informed, well thought-out, strategic decisions. According to the technical literature on MCDA, numerous methods are applicable in different decision-making situations, however, advice for selecting the most appropriate for the specific field of application and problem have not been thoroughly investigated. In land and real estate management, numerous queries regarding evaluations often arise. In brief, the objective of this paper is to outline a procedure with which to select the method best suited to the specific queries of evaluation, which commonly arise while addressing decision-making problems. In particular issues of land and real estate management, representing the so-called “settlement sector”. The procedure will follow a theoretical-methodological approach by formulating a taxonomy of the endogenous and exogenous variables of the multi-criteria analysis method

Decision support model for the selection of asphalt wearing courses in highly trafficked roads

The suitable choice of the materials forming the wearing course of highly trafficked roads is a delicate task because of their direct interaction with vehicles. Furthermore, modern roads must be planned according to sustainable development goals, which is complex because some of these might be in conflict. Under this premise, this paper develops a multi-criteria decision support model based on the analytic hierarchy process and the technique for order of preference by similarity to ideal solution to facilitate the selection of wearing courses in European countries. Variables were modelled using either fuzzy logic or Monte Carlo methods, depending on their nature. The views of a panel of experts on the problem were collected and processed using the generalized reduced gradient algorithm and a distance-based aggregation approach. The results showed a clear preponderance by stone mastic asphalt over the remaining alternatives in different scenarios evaluated through sensitivity analysis. The research leading to these results was framed in the European FP7 Project DURABROADS (No. 605404).The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under Grant Agreement No. 605404

Public initiatives of settlement transformation. A theoretical-methodological approach to selecting tools of multi-criteria decision analysis

In Europe, the operating context in which initiatives of settlement transformation are currently initiated is characterized by a complex, elaborate combination of technical, regulatory and governance-related factors. A similar set of considerations makes it necessary to address the complex decision-making problems to be resolved through multidisciplinary, comparative approaches designed to rationalize the process and treat the elements to be considered in systematic fashion with respect to the range of alternatives available as solutions. Within a context defined in this manner, decision-making processes must often be used to obtain multidisciplinary and multidimensional analyses to support the choices made by the decision-makers. Such analyses are carried out using multi-criteria tools designed to arrive at syntheses of the numerous forms of input data needed to describe decision-making problems of similar complexity, so that one or more outcomes of the synthesis make possible informed, well thought-out, strategic decisions. The technical literature on the topic proposes numerous tools of multi-criteria analysis for application in different decision-making contexts. Still, no specific contributions have been drawn up to date on the approach to take in selecting the tool best suited to providing adequate responses to the queries of evaluation that arise most frequently in the various fields of application, and especially in the settlement sector. The objective of this paper is to propose, by formulating a taxonomy of the endogenous and exogenous variables of tools of multi-criteria analysis, a methodology capable of selecting the tool best suited to the queries of evaluation which arise regarding the chief categories of decision-making problems, and particularly in the settlement sector

Biodiesel from microalgae : the use of multi-criteria decision analysis for strain selection

Microalgae strain selection is a vital step in the production of biodiesel from microalgae. In this study, Multi-Criteria Decision Analysis (MCDA) methodologies are adopted to resolve this problem. The aim of this study is to identify the best microalgae strain for viable biodiesel production. The microalgae strains considered here are Heynigia sp., Scenedesmus sp., Niracticinium sp., Chlorella vulgaris, Chlorella sorokiniana and Auxenochlorella protothecoides. The five MCDA methods used to evaluate different strains of microalgae are Analytic Hierarchy Process (AHP), Weighted Sum Method (WSM), Weighted Product Method (WPM), Discrete Compromise Programming (DCP) and Technique for the Order of Preference to the Ideal Solution (TOPSIS). Pairwise comparison matrices are used to determine the weights of the evaluation criteria and it is observed that the most important evaluation criteria are lipid content and growth rate. From the results, Scenedesmus sp. is selected as the best microalgae strain among the six alternatives due to its high lipid content and relatively fast growth rate. The AHP is the most comprehensive of the five MCDA methods because it considers the importance of each criterion and inconsistencies in the rankings are verified. The implementation of the MCDA methods and the results from this study provide an idea of how MCDA can be applied in microalgae strain selection

A Comparison of Multi-Criteria Decision Analysis Methods for Sustainability Assessment of District Heating Systems

Funding Information: Funding: This research was funded by the European Regional Development Fund within the project No. 1.1.1.2/VIAA/4/20/604 “Decision Support Tool for Decarbonisation Assessment of District Heating Systems (START)”. The contribution of E. Dace and R. Soloha to this study was supported by the University of Latvia within the project “Climate Change and its Impacts on Sustainability of Natural Resources” (No. Y5-AZ20-ZF-N-270). Publisher Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland.The sustainability of energy systems is increasingly assessed for development of more resilient, greener district heating (DH) systems. That requires compiling technological, environmental, and economic indicators in a social, political, and institutional context. This work investigates DH system sustainability analysis by five frequently applied multi-criteria decision analysis (MCDA) methods—WSM, TOPSIS, PROMETHEE, ELECTRE and DEA. To compare the sustainability assessment results, a selection of 8 criteria describing 12 DH companies (DHC) was examined. Sensitivity analysis was performed to determine the most credible MCDA method. Criteria weights were changed: (1) individually for evaluation of the range of stability for alternatives (score of DHC performance); (2) individually by a fixed value to compare how each criterion weight change affected the average score of a result; and (3) to compare the AHP weighting method to an equal weight scenario. The results of sensitivity analysis along with literature investigation shows that all methods are suitable for sustainability analyses of DH systems while also having differences in the calculation process and in the interpretation of results. The generalized algorithm for sustainability analysis in the energy sector outlined in this study along with the documented features of the main MCDA methods can be used as a guide for future assessment of energy systems by researchers and industry professionals.publishersversionPeer reviewe

Multi-Criteria Handover Using Modified Weighted TOPSIS Methods for Heterogeneous Networks

Ultra-dense small cell deployment in future 5G networks is a promising solution to the ever increasing demand of capacity and coverage. However, this deployment can lead to severe interference and high number of handovers, which in turn cause increased signaling overhead. In order to ensure service continuity for mobile users, minimize the number of unnecessary handovers and reduce the signaling overhead in heterogeneous networks, it is important to model adequately the handover decision problem. In this paper, we model the handover decision based on the multiple attribute decision making method, namely Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The base stations are considered as alternatives, and the handover metrics are considered as attributes to selecting the proper base station for handover. In this paper, we propose two modified TOPSIS methods for the purpose of handover management in the heterogeneous network. The first method incorporates the entropy weighting technique for handover metrics weighting. The second proposed method uses a standard deviation weighting technique to score the importance of each handover metric. Simulation results reveal that the proposed methods outperformed the existing methods by reducing the number of frequent handovers and radio link failures, in addition to enhancing the achieved mean user throughput

Prioritizing lean techniques by employing Multi-Criteria Decision-Making (MCDM): The case of MCoutinho

The business cycle in the automotive industry follows the general economic cycle closely and therefore, undergoes cyclical fluctuations over time. Companies in the sector are faced with challenges and need to deal with market demands efficiently and quickly to stay competitive. Lean approach is one of the strategies that can aid firms to improve their competitiveness by minimizing waste (Pullan et al., 2013). In order to benefit from a lean approach, the first step is to select a proper tool based on the available resources and requirements of the company. Due to the fact that numerous lean tools have been introduced over time, decision makers in company may encounter challenges in selecting the proper one with regard to their demands. To deal with such an issue, Multi-Criteria Decision-Making (MCDM) can greatly assist decision makers to compare available alternatives and consequently select the best possible solution among them. This study aims at improving the operational process in MCoutinho Group, a Portuguese well-known company in the automotive sector, by helping the management board in selecting lean tool due to the company preferences. In this study, the applicability (and results) of the application of some MCDM techniques (SAW, TOPSIS, and VIKOR) is examined to compare ten lean tools, determined based on the literature. The results reveal some gaps between company requirements and the demands which have been considered in previous surveys. The process applied can save the costs of trial and error of implementing different lean tools. And finally, adopting such a lean tool that has been selected totally based on the exclusive requirements of the company can improve efficiency in the company.O ciclo de negócios na indústria automotiva segue de perto o ciclo econômico geral e, portanto, sofre flutuações cíclicas ao longo do tempo. As empresas do setor enfrentam desafios e precisam lidar com as demandas do mercado de forma eficiente e rápida para se manterem competitivas. A abordagem enxuta é uma das estratégias que pode ajudar as empresas a melhorar sua competitividade, minimizando o desperdício (Pullan et al., 2013). Para se beneficiar de uma abordagem enxuta, o primeiro passo é selecionar uma ferramenta adequada com base nos recursos disponíveis e requisitos da empresa. Devido ao fato de que várias ferramentas enxutas foram introduzidas ao longo do tempo, os tomadores de decisão na empresa podem encontrar desafios ao selecionar a ferramenta adequada com relação às suas demandas. Para lidar com essa questão, a Tomada de Decisão Multi-Critérios (MCDM) pode ajudar muito os tomadores de decisão a comparar as alternativas disponíveis e, conseqüentemente, selecionar a melhor solução possível entre elas. Este estudo tem como objetivo melhorar o processo operacional do Grupo MCoutinho, empresa portuguesa de renome no setor automóvel, auxiliando a administração na seleção da ferramenta enxuta em função das preferências da empresa. Neste estudo, a aplicabilidade (e resultados) da aplicação de algumas técnicas MCDM (SAW, TOPSIS e VIKOR) é examinada para comparar dez ferramentas enxutas, determinadas com base na literatura. Os resultados revelam algumas lacunas entre os requisitos da empresa e as demandas consideradas em pesquisas anteriores. O processo aplicado pode economizar os custos de tentativa e erro de implementação de diferentes ferramentas enxutas. E, por fim, a adoção de uma ferramenta tão enxuta que foi selecionada totalmente com base nos requisitos exclusivos da empresa pode melhorar a eficiência da empresa

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