Multi-criteria Decision Analysis Methodology Research Articles

An ecotourism suitability index for a world heritage city using GIS-multi criteria decision analysis techniques

The concept of ecotourism has experienced a significant surge in popularity over the past two decades, primarily driven by the multitude of adverse impacts associated with mass tourism. The objective of the study was to develop a comprehensive ecotourism suitability index to guide policymakers in implementing tourism development policies. Given the considerable appeal of the study area to both local and international tourists, it is essential to conduct a systematic evaluation to pinpoint suitable areas for ecotourism development. This necessity arises from the study area's placement within a fragile ecosystem and its proximity to a UNESCO World Heritage site. We employed a Geographic Information Systems (GIS) integrated environment coupled with a fuzzy Multi-Criteria Decision Analysis (MCDA) methodology. The GIS-MCDA integrated framework leverages the Analytic Hierarchy Process (AHP) and a weighted linear combination that seeks to amalgamate many features and criteria to assess ecotourism potential by integrating 20 criteria into six separate categories: landscape, topography, accessibility, climate, forest and wildlife, and negative factors. Weights were allocated to each criterion and factor based on the expert's opinions of their impact on the development of ecotourism. The final ecotourism suitability index comprised five unique classes: very high, high, moderate, less, and not suitable. Results reveal that out of the total areas, 45.4 % (259 km2) are within the high and very high suitable classes. The sensitivity analysis suggested that ecotourism potentials are more favorable to forest and accessibility variables. The generated index can be utilized as a road map since validation verified a 64 % accuracy. Given the dearth of earlier research, this study provides vital support for the development of sustainable ecotourism projects in the study area.

Value contribution of blood-based neurofilament light chain as a biomarker in multiple sclerosis using multi-criteria decision analysis.

Multiple sclerosis (MS) is a chronic autoimmune demyelinating disease that represents a leading cause of non-traumatic disability among young and middle-aged adults. MS is characterized by neurodegeneration caused by axonal injury. Current clinical and radiological markers often lack the sensitivity and specificity required to detect inflammatory activity and neurodegeneration, highlighting the need for better approaches. After neuronal injury, neurofilament light chains (NfL) are released into the cerebrospinal fluid, and eventually into blood. Thus, blood-based NfL could be used as a potential biomarker for inflammatory activity, neurodegeneration, and treatment response in MS. The objective of this study was to determine the value contribution of blood-based NfL as a biomarker in MS in Spain using the Multi-Criteria Decision Analysis (MCDA) methodology. A literature review was performed, and the results were synthesized in the evidence matrix following the criteria included in the MCDA framework. The study was conducted by a multidisciplinary group of six experts. Participants were trained in MCDA and scored the evidence matrix. Results were analyzed and discussed in a group meeting through reflective MCDA discussion methodology. MS was considered a severe condition as it is associated with significant disability. There are unmet needs in MS as a disease, but also in terms of biomarkers since no blood biomarker is available in clinical practice to determine disease activity, prognostic assessment, and response to treatment. The results of the present study suggest that quantification of blood-based NfL may represent a safe option to determine inflammation, neurodegeneration, and response to treatments in clinical practice, as well as to complement data to improve the sensitivity of the diagnosis. Participants considered that blood-based NfL could result in a lower use of expensive tests such as magnetic resonance imaging scans and could provide cost-savings by avoiding ineffective treatments. Lower indirect costs could also be expected due to a lower impact of disability consequences. Overall, blood-based NfL measurement is supported by high-quality evidence. Based on MCDA methodology and the experience of a multidisciplinary group of six stakeholders, blood-based NfL measurement might represent a high-value-option for the management of MS in Spain.

Multi-criteria decision analysis framework for engaging stakeholders in river pollution risk management

Water pollution presents a substantial environmental challenge with extensive implications for water resources, ecosystem sustainability, and human health. Using a South African catchment, this study aimed to provide watershed managers with a framework for selecting best management practices (BMPs) to reduce pollution and the related risk to river users, while also including the perspectives of key catchment stakeholders. The framework encompassed the identification of and consultation with key stakeholders within the catchment. A Multi-Criteria Decision Analysis (MCDA) methodology using the Simple Multi-Attribute Rating Technique for Enhanced Stakeholder Take-up (SMARTEST) was used to identify and prioritise suitable BMPs in a case study. Decision alternatives and assessment criteria as well as their weights were derived based on stakeholder responses to a two-stage survey. Stakeholders included those utilising the river for domestic and recreational purposes, municipal representatives, scientists, NGOs, and engineers. The assessment of decision alternatives considered environmental, economic, and social criteria. The aggregated scores for decision alternatives highlighted the significance of involving stakeholders throughout the decision process. This study recommends the pairing of structural and non-structural BMPs. The findings provide valuable insights for catchment managers, policymakers, and environmental stakeholders seeking inclusive and effective pollution mitigation strategies in a catchment.

GeoValueIndex map of public property assets generating via Analytic Hierarchy Process and Geographic Information System for Mass Appraisal

The aim of this study is to develop a value-based GeoValueIndex with AHP weights and GIS for the criteria of the Mersin University (MEU) Çiftlikköy Campus real properties, and it is referred to as the “GeoValueIndex” in this study. GeoValueIndex is a symbolic value that combines geographic and non-geographic features of real properties. The data of the real properties on the campus were collected and arranged for mass appraisal. One of the Multi Criteria Decision Analysis (MCDA) methodologies, Analytic Hierarchy Process (AHP), was used to weight the criteria. GeoValueIndex was calculated by multiplying each parcel’s geographic and non-geographic data by their weights and adding them. GeoValueIndex Map is obtained by associating GeoValueIndex and parcel in GIS software. GeoValueIndex of real properties save time, effort, and cost in mass appraisal processes. There are many techniques for doing GeoValueIndex operations, and the ones presented in this study are only proposals.

Holistic approaches for risk-benefit assessment

Abstract Moving towards holistic approaches that assess trade-offs among health, sustainability, and economics is imperative to minimize emergent risks and drivers of environmental degradation associated with food systems. Health risk-benefit assessments provide informative outputs to support decision-making within the public health domain. However, integrating indicators from different dimensions requires tailoring current risk-benefit methods. In this context, multicriteria decision analysis methodologies can be relevant to account for different factors and weighing trade-offs of real-life scenarios of changes in food systems. In addition, further research building on initiatives attempting to integrate frameworks within health (e.g., risk analysis) and environment (e.g., Life-Cycle Assessment and linear programming) or health and economics (e.g., cost-benefit and cost of illness), is needed to establish a holistic risk-benefit assessment framework. This presentation will introduce current efforts in the development of holistic assessment methods that evaluate impacts beyond the health risk and benefits perspective. In addition, the presentation will highlight the potential gains of such methods in policymaking.

Using the analytical hierarchical process for programme design decisions: A disability case study

Background: A care facility for people with disabilities struggles to obtain financial support for its Parent Education and Support Programme. The programme’s design includes two implementers, an occupational therapist and a community-based worker, increasing its core costs. To enhance the likelihood of donor support, the Facility considered choosing the best-suited implementer for the programme. To help inform this decision, a formal methodological approach to high-level decision-making called multi-criteria decision analysis (MCDA) was utilised.Objective: Through a case study, this paper demonstrates how the MCDA methodology, using the analytical hierarchical process (AHP), was applied in a programme evaluation context.Method: Decision models were constructed using the AHP MCDA method and elicited rater judgments. Raters were drawn from four stakeholder groups: Programme beneficiaries, management, donors, and experts in disability and rehabilitation. This was followed by assigning criteria weights, establishing local priorities for each alternative, and aggregating the judgments. The model was then synthesised, and a sensitivity analysis was conducted.Results: The findings revealed that specific outcomes were attributed to each implementer, and thus, deciding to employ only one implementer would have had serious consequences for the programme’s quality and the achievement of intended outcomes.Conclusion: The results confirmed the usefulness of AHP MCDA for programme design decisions.Contribution: This article contributes by enhancing the understanding of the AHP MCDA methodology. Secondly, it demonstrates the suitability of this methodology for programme designers, evaluators, or non-profit organisations (NPOs) who need to make informed decisions about the design and implementation of interventions.

A GIS-MCDA-Based Analysis for Spatial Ecotourism Suitability Assessment in Saudi Arabia’s Hail Province

Ecotourism was developed to combine culture, education, and tourism, but it has now evolved into a fundamental idea for global ecological sustainability. Ecotourism has the potential to help protect natural assets while also fostering beneficial synergies among tourism sector agents, visitors, and local residents. Low-density communities gain from rising interest in low-impact tourist products that assist the local economy. Based on this approach, the current research aims to assess the potential of existing natural and rural characteristics in the Hail area, situated in the center of Saudi Arabia, to underpin the development of sustainable tourist goods. In the research, natural ecotourism locations in Saudi Arabia’s Hail province were evaluated for their spatial suitability. The methodology of the research included a number of steps and procedures, beginning with the creation of a geographic database on the area’s natural resources for tourists. After extracting data from various sources and determining the criteria for the spatial suitability of natural tourist sites, which are represented in a set of natural and human criteria that directly affect the success of any tourist site based on the standards of the Saudi Commission for Tourism and National Heritage, the Ministry of Municipal and Rural Affairs and Housing, and standards derived from literary references, a total of 27 highly suitable sites were identified. Based on GIS (Geographic Information System)-based multicriteria decision analysis (GIS-MCDA) methodology, nine criteria were identified and represented in the form of layers, which were merged with each other through the overlay mechanism, after assigning a weight to each criterion based on its importance, to create a map identifying relevant natural environment tourist locations in the research region. The locate region for ecotourism, which covers 24501.225 km2, produced by the suitability modeler tool within ArcGIS Pro software and defined by the presence of ecotourism sites that fulfill the needs and standards of environmental tourism sites according to four degrees of suitability (high, moderate, marginal, and low). From a total of 64 sites, 27 exhibit a high suitability for ecotourism, accounting for 42.18% of all sites. While the number of sites with a moderate suitability rating reached 37 sites, representing 57.81% of all sites.

Large-scale real-life implementation of technology-enabled care to maximize hospitals' medical surge preparedness during future infectious disease outbreaks and winter seasons: a viewpoint.

Hospitals can be overburdened with large numbers of patients with severe infectious conditions during infectious disease outbreaks. Such outbreaks or epidemics put tremendous pressure on the admission capacity of care facilities in the concerned region, negatively affecting the elective program within these facilities. Such situations have been observed during the recent waves of the coronavirus disease pandemic. Owing to the imminent threat of a "tripledemic" by new variants of the coronavirus disease (such as the new Omicron XBB.1.16 strain), influenza, and respiratory syncytial virus during future winter seasons, healthcare agencies should take decisive steps to safeguard hospitals' surge capacity while continuing to provide optimal and safe care to a potentially large number of patients in their trusted home environment. Preparedness of health systems for infectious diseases will require dynamic interaction between a continuous assessment of region-wide available hospital capacity and programs for intensive home treatment of patients who can spread the disease. In this viewpoint, we describe an innovative, dynamic coupling system between hospital surge capacity and cascading activation of a nationwide system for remote patient monitoring. This approach was developed using the multi-criteria decision analysis methodology, considering previously published real-life experiences on remote patient monitoring.

Value contribution of cenobamate for the treatment of Focal-Onset Seizures (FOS) in patients with drug-resistant epilepsy (DRE) in Spain through reflective Multi-Criteria Decision Analysis (MCDA)

IntroductionEpilepsy is one of the most common neurological conditions worldwide. The main goal of its treatment is to achieve seizure freedom without intolerable adverse effects. However, despite the availability of many anti-seizure medications, including the latest options, called third-generation anti-seizure medications (ASMs), approximately 40% of people with epilepsy present drug-resistant epilepsy (DRE). Cenobamate is the first ASM approved in Spain for the adjunctive treatment of Focal-Onset Seizures (FOS) in adult patients with DRE. In a chronic disease with a portfolio of available ASMs, the decision to introduce a new therapeutic alternative must follow a holistic evaluation of value provided. Reflective Multi-Criteria Decision Analysis (MCDA) methodology allows to determine the value contribution of a treatment in a given indication considering all relevant criteria for healthcare decision-making in a transparent and systematic manner from the perspective of relevant stakeholders. PurposeThe aim of this study was to determine the relative value contribution of cenobamate in the treatment of FOS in patients with DRE compared with third-generation ASMs using reflective MCDA-based methodology. MethodsA systematic literature review (combining biomedical databases and grey literature sources) was performed to populate the Evidence and Value: Impact on DEcisionMaking (EVIDEM) MCDA framework adapted to determine what represents value in the management of FOS in patients with DRE in Spain. The study was conducted in two phases. The first took place in 2021 with a multi-stakeholder group of eight participants. The second phase was conducted in 2022 with a multi-stakeholder group of 32 participants. Participants were trained in MCDA methodology and scored four evidence matrices (cenobamate vs. brivaracetam, vs. perampanel, vs. lacosamide and vs. eslicarbazepine acetate). Results were analyzed and discussed in a group meeting through reflective MCDA discussion methodology. ResultsDRE is considered a very severe condition associated with many important unmet needs, mainly with regard to the lack of more effective treatments to achieve the ultimate goal of treatment. Compared to third-generation ASMs, cenobamate is perceived to have a better efficacy profile based on improvements in responder rate and seizure freedom. Regarding safety, it is considered to have a similar profile to alternatives and a positive quality-of-life profile. Cenobamate results in lower direct medical costs (excluding pharmacological) and indirect costs. Overall, cenobamate is regarded as providing a high therapeutic impact and supported by high-quality evidence. ConclusionsBased on reflective MCDA methodology and stakeholders’ experience in clinical management of epilepsy in Spain, cenobamate is perceived as a value-added option for the treatment of patients with DRE when compared with third-generation ASMs.

Multi-criteria decision-making framework on process water treatment of minimally processed leafy greens

The use and application possibilities of the multi-criteria decision analysis (MCDA) methodology, as a decision support tool in food safety risk management was demonstrated in a case study on the washing of minimally processed leafy greens, a multidimensional food safety decision problem involving public health, economic, environmental and socio-cultural aspects. The washing procedure remains a critical step in the production chain of ready-to-eat leafy vegetables, as the process water could act as a vector for cross-contamination of pathogens. The use of chemical sanitizers in produce wash water is scattered over EU member states and regulations remain unharmonized. The most appropriate washing methodology was determined, for the Belgian situation, based on an evaluation of weighted criteria, following the PROMETHEE II algorithm. Hereto multiple sources of information were consulted, including scientific and grey literature, expert evaluations and information provided by vegetable processing companies. Data generated over the past 10 years and published in scientific literature were selected and aggregated into probabilistic distributions using @Risk® software. An online stakeholder consultation, organized in Belgium, had the aim to measure stakeholders' preferences. The MCDA case study indicated that washing leafy greens in potable (ice) water, should be considered the most appropriate method for the Belgian case. The MCDA methodology can be applied for building evidence-based risk management decisions in the field of food safety, as it provides a transparent framework for the collection of evidence and the inclusion of stakeholders' interests.

A Decision-Making Framework for Assessing New Rate Mechanisms: The Case of US Gas Distributors

<p><big>To make an assessment of ratemaking proposals, this article proposes that regulators should consider applying a logical decision-making process, such as multi-criteria decision analysis (MCDA), that selects or modifies those rate mechanisms that come closest to achieving the public interest, as defined by regulators. MCDA seems like an fitting tool to improve regulatory decisions by making more explicit the relationship between different rate mechanisms and the public interest. This article provides a simplified version of MCDA to demonstrate how regulators can apply this tool to evaluate new rate mechanisms in terms of the public interest. As far as the author knows, the MCDA methodology applied to utility ratemaking has not appeared in the literature. While regulators may not want to or lack the resources to execute all the steps presented in this article, MCDA can provide direction to regulators in evaluating different rate mechanisms and ultimately reaching decisions that are more rational and aligned with the public interest. After all, evaluating rate mechanisms is one of the major functions of utility regulators. Doing it wrongly can have a consequential effect on society’s welfare.</big></p>

Multi-Criteria Decision Analysis for Assessing Social Acceptance of Strategies to Reduce Antimicrobial Use in the French Dairy Industry.

To respond to the antimicrobial resistance (AMR) threat, public health entities implement policies aiming to reduce antimicrobial use (AMU) in livestock systems, in which policy success and sustainability might be subject to the social acceptability of the novel regulatory environment. Therefore, consistent methods that gather and synthesize preferences of stakeholder groups are needed during the policy design. The objective of this study was to present a methodology for evaluating the acceptability of potential strategies to reduce AMU using multi-criteria decision analysis (MCDA) using French dairy industry as a model. Preference-ranking organization methods for enrichment evaluations were applied to rank stakeholders' acceptance of four different potential AMU reduction strategies: 1. Baseline AMU regulations in France; 2. Total interdiction of AMU; 3. Interdiction of prophylaxis and metaphylaxis AMU; and 4. Subsidies to reduce AMU by 25%. A total of 15 stakeholders (consumers, n = 10; farmers, n = 2; public health representatives, n = 3) representing the French dairy sector and public health administration participated in the acceptance weighting of the strategies in relation with their impact on environmental, economic, social, and political criteria. We established a MCDA methodology and result-interpretation approach that can assist in prioritizing alternatives to cope with AMR in the French dairy industry or in other livestock systems. Our MCDA framework showed that consumers and public health representatives preferred alternatives that consider the restriction of AMU, whereas farmers preferred to maintain baseline policy.

Dealing with multi-criteria decision analysis in time-evolving approach using a probabilistic prediction method

Multi-criteria Decision Analysis (MCDA) is a methodology that has been classically used to rank alternatives according to a set of decision criteria. The MCDA techniques have been shown to be an efficient tool in a number of real-life engineering problems. Nevertheless, most of the proposed approaches in the field do not consider the temporal characteristic of the criteria values, which can be an interesting information to be explored in order to predict future rankings. The present work proposes a novel MCDA methodology in which the past data of the criteria are considered to predict their future values. Our approach is based on a tensorial formulation, together with the use of the recursive least mean squares method in the prediction step. In addition, we consider a probabilistic prediction and use the Stochastic Multi-criteria Acceptability Analysis, which allows the decision maker to observe the degree of uncertainty in the ranking. Numerical experiments with synthetic and actual data attest to the proposal’s relevance in scenarios in which the criteria values change over time.

Flood Susceptibility in the Lower Course of the Coyuca River, Mexico: A Multi-Criteria Decision Analysis Model

Flooding due to climate change is recurrent and has intensified in the lower course of the Coyuca River. This paper implements a multivariate analysis, including conditioning and triggering factors to develop flood susceptibility mapping in an information-deprived region to help prevent/mitigate flooding. Flood-susceptible areas were identified using the multi-criteria decision analysis (MCDA) methodology, specifically, with the hierarchy analysis process (AHP). Four conditioning and one triggering influence factors were analyzed. The influence weights of each variable were determined using Saaty’s methodology (AHP). Thematic maps for each variable were created and multiplied by their influence value using the raster calculator and added to their variable group to obtain the flood susceptibility map. The findings showed that the susceptibility to flooding was very high in 41.82%, high in 35.95%, medium in 21.25% and low in 0.98% of the study areas. It was revealed that 44.44% of the localities occupy areas of very high susceptibility to flooding. Susceptibility increases in the localities closest to the river.

A multicriteria decision analysis framework for developing and evaluating coastal retreat policy.

Managed retreat may be a necessity for coastal communities as sea levels rise due to climate change. Selecting the right policy decisions and timing is difficult given the vested interests of communities and stakeholder groups and requires careful balancing of the benefits and risks associated with each management alternative. State and federal agencies often employ single-objective optimization frameworks such as cost-benefit analysisto analyze coastal relocation alternatives, but such methods are limited in their ability to balance competing value considerations and stakeholder demands. The use of a multicriteria decision analysis (MCDA) methodology allows for such considerations to be quantified and evaluated, thereby improving planning and decision-making for coastal retreat policies. This paper provides a strategic MCDA framework to evaluate coastal retreat policy that could be leveraged by at-risk coastal communities. The MCDA is applied to a hypothetical coastal retreat scenario to visualize policy preferences and differing value considerations among stakeholders. This model can be used by government agencies to foster more sound, acceptable, and implementable coastal retreat policies and streamline the incorporation of this climate adaptation mechanism, which may be necessary for the near future. Integr Environ Assess Manag 2023;19:83-98. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Valor de la hemodiálisis concertada y la hospitalaria mediante un análisis de decisión multicriterio

ObjectiveTo evaluate the value of the provision of contracted versus hospital dialysis services for the treatment of chronic kidney disease in Spain using the multicriteria decision analysis methodology. MethodThe EVIDEM (Evidence and Value: Impact on Decision Making) evaluation framework was used to calculate the estimated value of both dialysis delivery models (arranged vs. hospital) through a virtual workshop in which different profiles participated: directors and managers, professionals and heads of units and representatives of patients and relatives. The scores were combined using an additive lineal model, which combined the weight of the model with the individual score of the criteria, and each value was transformed to a scale between 0 and 1. ResultsThe estimated value for arranged dialysis was 0.29 (DS: ±0.2) and 0.39 (DS: ±0.2) for hospital dialysis. All profiles gave a higher value to hospital hemodialysis compared to contracted hemodialysis. The highest value for hospital dialysis was for patients (0.44), with the lowest mean value for directors (0.36) and the range for arranged dialysis being between patients (0.31) and intermediate positions (0.27). ConclusionsHospital hemodialysis obtained a higher value than concerted dialysis. In general, the panelists affirmed that it is a useful and interesting exercise and that, to a certain extent, it provides security in decision-making, since it allows ordering, rationalizing and considering, in an explicit and transparent manner, the different criteria involved.

Evidence-based land conservation framework using multi-criteria acceptability analysis: A geospatial tool for strategic land conservation in the Gulf coast of the United States

Strategic land conservation investments that prioritize stakeholder priorities show promise for protection of ecological integrity and associated socioeconomic benefits of land conservation. However, despite many known benefits, decisions on where and what to conserve are often made without effective ecological and socioeconomic considerations. Ideally, multiple measurable attributes relevant to the ecological and socioeconomic priorities of stakeholders should be brought into an efficient, data-driven framework to evaluate areas of interest and help optimize decisions on conservation investments. Planners need to have access to a dynamic, web-based platform that assesses and compares conservation areas based on geospatial, science-based, and stakeholder-driven data. In this work, we provide a co-produced framework for a multi-criteria Conservation Prioritization Tool (CPT) that is based on available geospatial data reflecting stakeholder priorities for land conservation. The framework allows for flexible and hierarchical weighting of goals and data measures by the decision maker and allows for optimization of conservation decisions through a geospatial multi-criteria decision analysis (MCDA). Geospatial MCDA is a popular approach for evaluating decision alternatives in conservation problems, but the scarcity of functional tools that are widely accessible still limits their breadth of use. In this work, we describe the structure and creation of the CPT and demonstrate its application in the United States Gulf of Mexico coastal region, an area over 700,000 km2 in size. We designed and implemented a dynamic, cloud-based software tool that both considers and ranks user priorities and utilizes geospatial MCDA to evaluate areas of interest for land conservation. This tool improves the effectiveness and efficiency of land conservation actions by reducing the time needed to gather ecological evidence, increasing the transparency of decision processes, and encouraging inter-organizational partnerships. The versatile and open-access nature of the CPT broadens the availability of the geospatial MCDA methodology for conservation planners across large regions. We intentionally developed the CPT framework and procedures therein to be transferable and open-source to other objectives for any desired spatial geography.

Protocol: Systematic literature review of the application of the multicriteria decision analysis methodology in the evaluation of urban freight logistics initiatives

The paper presents a protocol for conducting a systematic literature review (SLR) on the application of multicriteria decision analysis methods (MCDM) as a tool for evaluating urban freight logistics. The paper presents a protocol for conducting a systematic literature review (SLR) on the application of multicriteria decision analysis methods (MCDM) as a tool for evaluating urban freight logistics.This research topic arises from the growing interest of public and private actors in achieving objectives of reducing environmental and social impacts and/or improving operational efficiency in city logistics.The search is focused on publications comprised in the period between 2012 and 2020. Finally, with the selected works, a descriptive analysis is carried out, which allows obtaining a preliminary result of the RSL that will be developed in future research.SDGs' supported by research: SDG08 Decent Work and Economic Growth and SDG11 Sustainable Cities and Communities.

Hybridization of genetic algorithm and fuzzy based TOPSIS method to solve the robot path planning problem for multi objectives

A variety of approaches are employed to solve the Mobile Robot Path Planning Problem (MRPP), which is the essential domain of research from industrial automation to domestic appliances. Since MRPP is categorized as an NP-hard problem, non-deterministic approaches are preferred to obtain optimal results. The Genetic Algorithm(GA) is the popular methodology for determining the optimal path for robot navigation. The complexity increases in finding the optimal path for the MRPP problem, if more than one objective is to be considered. To reduce the complexity, one of the multi-criteria decision analysis (MCDA) methodologies with fuzzy logic is hybridized to solve MRPP without losing the advantage of the GA approach. In this article, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is employed for determining the best path out of given paths. As a preprocessing of the population, a Genetic Algorithm (GA) is employed, which is having the advantage of exploring the population with crossover, mutation, and selection operators. The output of the GA is given to the Fuzzy TOPSIS method where the degree of preference is given as the linguistic variable.

Multi-expert multi-criteria decision analysis model to support the conservation of paramount elements in industrial facilities

The coupling of urban retrofitting with climate change adaptation and environmental conservation is impacting on current industrial activities such as electricity production based on fossil fuels. Therefore, new tools are required to support adaptive reuse towards the conservation of industrial facilities, in order to leave testament of their cultural and industrial heritage once their production activities cease to exist. Multi-Criteria Decision Analysis (MCDA) can help analyse complex interactions between industrial elements, society, culture and nature, providing key benefits when approaching heritage investigations. In this context, this research concerned the design of a Multi-Expert MCDA (ME-MCDA) methodology to support the selection of paramount heritage elements in power plants based on the collection and processing of the views of a panel of experts to result in consensus groups. This approach was tested using a case study in the As Pontes power plant (NW Spain), which will be dismantled in a near future. The results achieved pointed out to cooling towers, boilers, chimney and turbine hall as the fundamental elements to preserve due to their relevance across a set of technical, historical and sociocultural criteria. These outcomes proved the usefulness of the proposed approach in favouring the valorisation of industrial facilities as heritage areas protecting the social and cultural history of a territory.