Analytic Hierarchy Process Multi-criteria Decision Research Articles

Aligning the Goals Hybrid Model for the Diagnosis of Mental Health Quality

The social distancing imposed by the COVID-19 pandemic has been described as the “greatest psychological experiment in the world”. It has tested the human capacity to extract meaning from suffering and challenged individuals and society in Brazil and abroad to promote cohesion that cushions the impact of borderline experiences on mental life. In this context, a survey was conducted with teachers, administrative technicians, and outsourced employees at the Federal Institute of Piauí (IFPI). This educational institution offers professional and technological education in Piauí, Brazil. This study proposes a system for the early diagnosis of health quality during social distancing in the years 2020 and 2021, over the COVID-19 pandemic, combining multi-criteria decision support methodology, the Analytic Hierarchy Process (AHP) with machine learning algorithms (Random Forest, logistic regression, and Naïve Bayes). The hybrid approach of the machine learning algorithm with the AHP multi-criteria decision method with geometric mean accurately obtained a classification that stood out the most in the characteristics’ performance concerning emotions and feelings. In 2020, the situation was reported as the SAME AS BEFORE, in which the hybrid AHP with Geographical Average with the machine learning Random Forest algorithm stands out, highlighting the atypical situation in the quality of life of the interviewees and the timely manner in which they realized that their mental health remained unchanged. After that, in 2021, the situation was reported as WORSE THAN BEFORE, in which the hybrid AHP with geometric mean with the machine learning Random Forest algorithm provided an absolute result.

A Socio-economic Indicator for EoL Strategies for Bio-based Products

In recent years, the bioeconomy has received increased attention from policy makers and practitioners, leading to a first switch from fossil to bio-based products. To open up new market opportunities, transparent information on the sustainability of bio-based products must be provided, taking into account all life cycle stages. The determination of suitable end of life (EoL) strategies furthers this aim. Notably, the socio-economic aspects of EoL alternatives associated with bio-based products have been neglected. This paper contributes to filling this gap by proposing a new socio-economic indicator for EoL (SEI-EoL). The SEI-EoL is developed from an integrated analytic hierarchy process–multicriteria decision analysis (AHP-MCDA) model based on experts' involvement, and is capable of measuring and comparing the socio-economic performance of EoL alternatives for bio-based products. The SEI-EoL is applied to the specific case of polylactic acid (PLA)–based film for food packaging. The results indicate that value chain actors are the most influential category of stakeholders in EoL management, and the assessment of criteria shows that waste disposal cost, resource efficiency and EoL responsibility play a key role in this management. The highest value EoL strategy for PLA-based film for food packaging is mechanical recycling, followed by chemical recycling. Circularity assessment, policy maker responsibility and incentives for recycled materials/green processes represent the most relevant items to consider for policy recommendations and actions.

Performance analysis of fuzzy analytic hierarchy process multi-criteria decision support models for contractor selection

Multi-Criteria Decision Making (MCDM) is a discipline aimed at supporting decision-makers to settle on an ideal choice within the sight of different and clashing criteria. MCDM strategies have developed to oblige different kinds of utilizations. One comprehensively utilized MCDM strategy is the Analytic Hierarchy Process (AHP). AHP, in spite of its simplicity in idea, it can't consider imprecise input. Throughout the years, fuzzy logic has demonstrated its effectiveness as a MCDM technique. It includes a few preferences inside uncertain, imprecise and obscure settings than AHP and other MCDM strategies. Consolidating Fuzzy strategies with AHP is one methodology for taking care of the entangled issues of AHP. The significance of this study is to provide baseline information to the construction clients and consultants on the importance of contractor's prequalification decision criteria to be adopted, which will eventually translate to a better decision making and increase project performance. Taking into account our past research, this paper proposed a Feedback Integrated Fuzzy Analytic Hierarchy Process (FAHP) model for ranking decision criteria for contractual worker determination by combining the selection process and consistency control module. This consistency control module contains a feedback module that generates advice to decision makers so as to check the irregularity in their decisions' during pairwise comparisons. In this paper, the performance investigation of the proposed FAHP model is validated on datasets from three diverse FAHP models. The proposed model accuracy obtained when tested with three distinctive datasets were 98.2%, 99.99%, and 98.24% respectively. The results established the adequacy and uselfulness of the proposed FAHP model in ranking contractor decision criteria. The research additionally guide decision-makers on picking distinctive FAHP algorithms in assessing and ranking decision criteria utilized in contractors selection.

Multi-criteria decision-making for sustainable metropolitan cities assessment

The recent development of metropolitan cities, especially in Europe, requires an effective integrated management of city services, infrastructure, and communication networks at a metropolitan level. A preliminary step towards a proper organizational and management strategy of the metropolitan city is the analysis, benchmarking and optimization of the metropolitan areas through a set of indicators coherent with the overall sustainability objective of the metropolitan city. This paper proposes the use of the Analytic Hierarchy Process multi-criteria decision making technique for application in the smart metropolitan city context, with the aim of analysing the sustainable development of energy, water and environmental systems, through a set of objective performance indicators. Specifically, the 35 indicators defined for the Sustainable Development of Energy, Water and Environment Systems Index framework are used. The application of the approach to the real case study of four metropolitan areas (Bari, Bitonto, Mola, and Molfetta) in the city of Bari (Italy) shows its usefulness for the local government in benchmarking metropolitan areas and providing decision indications on how to formulate the sustainable development strategy of the metropolitan city. Based on the Analytic Hierarchy Process characteristics, the results highlight that although one specific area (Mola in the considered case) is globally ranked at the first place, it is only ranked first with respect to some dimensions. Such a result has strong implications for the metropolitan city's manager who has the possibility to identify and implement targeted actions, which may be designed ad hoc to improve specific dimensions based on the current state of the city, thus maximizing the efficiency and effectiveness of the actions undertaken for the sustainable development of energy, water and environmental systems of the whole metropolitan city.

Multi-criteria decision analysis for renewable energy integration: A southern India focus

In recent days, sustainability is considered as an important mechanism due to contemporary increase in demands and worldwide limited resources. This paper presents the possibility of integrating a renewable energy system with an existing grid to meet electrical energy demand of institutional buildings located in Indian state of Tamil Nadu. Currently, the Tamil Nadu state electric-grid power is not surplus and experiencing 40% short fall in generation. In this present paper a modern approach for the optimum planning of electric power system (EPS) is proposed based on the Analytic Hierarchy Process (AHP). An intertwined analysis on energy management and techno-economic optimization of grid connected renewable energy system is proposed. The prospects of different fixed tilt solar panels and peak load shifting based energy management are performed through HOMER Energy® simulation. The AHP multi-criteria decision analysis reveals that annual optimum tilt grid connected photovoltaic system is the optimum configuration for study location. The effectiveness of the AHP approach is evaluated with best-worst method and stochastic multi-criteria acceptability analysis for prioritizing the renewable energy system options in order to select best EPS. In addition, the optimum configuration is implemented in the institutional buildings and performance is analyzed under varying climatic conditions.

Prioritization of Reputation Loss Factors Imposed By Pipeline Failure Subject to Corrosion

Reputation loss of a pipeline failure subject to corrosion is commonly neglected due to its qualitative nature. However, case studies found that perceptions of the stakeholders are prone to affect pipeline owner’s long-term reputation. Identifying the influence factors is insufficient to assist the owner to respond if pipeline failure occurs. Thus, this article endeavors to prioritize the influential reputation loss factors by interviewing six experts of pipeline integrity management personnel. The analytic hierarchy process multi-criteria decision making method was selected to help the prioritization process. Result shows that the most influenced factor is the loss of customer confidence (B1) and employee(s) caused accident (C9) ranked the least. The effort to quantify reputation loss can be substituted by prioritizing them according to stakeholders’ preferences as an initial step to monetarily quantify these factors in future. Thus, a comprehensive pipeline risk assessment and the pipeline integrity management can be achieved and simultaneously improve the company’s annual profit margin .

Geomarketing techniques to locate retail companies in regulated markets

Our background is the investment when opening a retail business in a regulated market, such as the pharmaceutical sector in Spain, which involves many risks caused by external factors that hinder the choice of a new-business location process. To study this phenomenon, we optimized the choice of the location of a retail site in a regulated market via a methodology that entailed a combination of analytical methods of spatial geometry with geographic information systems (GIS) and the analytic hierarchy process (AHP) multicriteria decision method. The integration of both methods shows great efficiency in the measurement of spatial reality in detail and its influence on decision-making in retail businesses. The study, conducted in Seville (Spain), showed how legal restrictions for the location of a new pharmacy greatly hindered the possibility of success for new retail businesses. However, by implementing both methods, we discovered a series of suitable spaces, which were assigned a score based on several criteria. The combination of GIS methods and AHP multicriteria decision method can be used to reduce the risk of opening a new retail business in a regulated market with space restrictions.