A web-based multiple criteria decision support system for evaluation analysis of carpooling

Petrillo, Antonella; Carotenuto, Pasquale; Baffo, Ilaria; Felice, Fabio De

doi:10.1007/s10668-017-9991-z

Cited by 13 publications

(6 citation statements)

References 38 publications

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“…2016 Transportation High Quality [90] In this study, a multi-criteria decision support system (MDSS) is developed for carpooling problems. The presented system is a web-based multi-criteria decision support system.…”

Section: Transportationmentioning

confidence: 99%

Intelligent Decision Support Systems—An Analysis of Machine Learning and Multicriteria Decision-Making Methods

Ali,

Hussain,

Nazir

et al. 2023

Applied Sciences

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Context: The selection and use of appropriate multi-criteria decision making (MCDM) methods for solving complex problems is one of the challenging issues faced by decision makers in the search for appropriate decisions. To address these challenges, MCDM methods have effectively been used in the areas of ICT, farming, business, and trade, for example. This study explores the integration of machine learning and MCDM methods, which has been used effectively in diverse application areas. Objective: The objective of the research is to critically analyze state-of-the-art research methods used in intelligent decision support systems and to further identify their application areas, the significance of decision support systems, and the methods, approaches, frameworks, or algorithms exploited to solve complex problems. The study provides insights for early-stage researchers to design more intelligent and cost-effective solutions for solving problems in various application domains. Method: To achieve the objective, literature from the years 2015 to early 2020 was searched and considered in the study based on quality assessment criteria. The selected relevant literature was studied to respond to the research questions proposed in this study. To find answers to the research questions, pertinent literature was analyzed to identify the application domains where decision support systems are exploited, the impact and significance of the contributions, and the algorithms, methods, and techniques which are exploited in various domains to solve decision-making problems. Results: Results of the study show that decision support systems are widely used as useful decision-making tools in various application domains. The research has collectively studied machine learning, artificial intelligence, and multi-criteria decision-making models used to provide efficient solutions to complex decision-making problems. In addition, the study delivers detailed insights into the use of AI, ML and MCDM methods to the early-stage researchers to start their research in the right direction and provide them with a clear roadmap of research. Hence, the development of Intelligent Decision Support Systems (IDSS) using machine learning (ML) and multicriteria decision-making (MCDM) can assist researchers to design and develop better decision support systems. These findings can help researchers in designing more robust, efficient, and effective multicriteria-based decision models, frameworks, techniques, and integrated solutions.

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Section: Transportationmentioning

confidence: 99%

Intelligent Decision Support Systems—An Analysis of Machine Learning and Multicriteria Decision-Making Methods

Ali,

Hussain,

Nazir

et al. 2023

Applied Sciences

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show abstract

“…However, cost-benefit analysis is also usually a complex decision-making problem in the presence of multiple objectives and the constraints are often not explicit. In these cases, the use of multicriteria analysis models (MCDM) allows one to compare and order the alternatives present in the problem on the basis of data referring to objectives that are often in contrast with each other [47]. The multi-criteria analysis aims to provide support to the decision maker to achieve an acceptable compromise between the various objectives pursued.…”

Section: Directions For Further Researchmentioning

confidence: 99%

The Cost Benefit Analysis of Commercial 100 MW Solar PV: The Plant Quaid-e-Azam Solar Power Pvt Ltd.

et al. 2022

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The energy crisis in Pakistan has crippled the country’s economy with an energy shortfall reaching up to 6000 MW. Fortunately, Pakistan lies close to the Sun Belt and therefore receives very high irradiation. To this end, in the beginning of 2014 the Pakistani government sanctioned a solar photovoltaic project namely Quaid-e-Azam Solar Park which was rated at 1000 MW. In this study, a cost benefit analysis for the Quaid-e-Azam Solar Park has been developed. The model uses RETScreen software. In fact, a literature review pointed out that most of the previous research work with reference to cost benefit analysis for solar projects has been mainly carried out on smaller power plants. The outcome of the study shows promising results with the simple payback period coming out at 5.6 years. Furthermore, this analysis can serve as guideline for future solar photovoltaic projects in Pakistan and can help in the development and utilization of the huge solar potential of the country, thus aiding in the reduction of energy shortage. In its proposal, our research is unique and innovative in the Pakistani context. The results aim to serve as a guideline for decision makers and researchers interested in this topic.

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“…Rahman et al (2019) used AHP with ratings to propose a system of business excellence aimed at the Bangladesh hotel industry. In another example of the application of this approach, Petrillo et al (2018) developed a carpooling system platform model based on different criteria.…”

Section: Ahp With Ratingsmentioning

confidence: 99%

Evaluation of the socioeconomic and environmental sustainability of banking institutions in Brazil using the Analytic Hierarchy Process with ratings approach

et al. 2021

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Large banking institutions play an important role in sustainable development, especially owing to their size and capillarity. Therefore, the objective of this study is to compare sustainability indicators (economic, environmental, and social) published in the reports of some of these institutions that operate in the Brazilian market. The four banks selected for this study were the ones that published their sustainability reports in the 2017 Global Reporting Initiative standard, and that comprised the portfolio of the Corporate Sustainability Index, promoted by “Brasil, Bolsa e Balcão,” in 2018. These banks were Banco do Brasil, Bradesco, Itaú, and Santander. The analytic hierarchy process (AHP) with the use of ratings was used to carry out the research. After elaborating on the hierarchical structure of the problem, specialists, who were researchers in the field of sustainability, were required to weigh the degree of relevance of each of the indicators analyzed in this study. A ranking of the selected banks was then obtained in relation to their sustainability performances, which was based on the weights given to each indicator and the data available in the sustainability reports of each institution investigated. The banks were ranked in the following order: Itaú, Santander, Bradesco, and Banco do Brasil. The results of this study showed that there is room for evolution in relation to sustainability, mainly in the social department, in the banking sector. The AHP method with the use of ratings proved to be efficient, especially because it allowed for the weighing of the evaluation criteria and sub-criteria; this proved the usefulness of the method in comparing companies with regard to their sustainability performance.

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A web-based multiple criteria decision support system for evaluation analysis of carpooling

Cited by 13 publications

References 38 publications

Intelligent Decision Support Systems—An Analysis of Machine Learning and Multicriteria Decision-Making Methods

Intelligent Decision Support Systems—An Analysis of Machine Learning and Multicriteria Decision-Making Methods

The Cost Benefit Analysis of Commercial 100 MW Solar PV: The Plant Quaid-e-Azam Solar Power Pvt Ltd.

Evaluation of the socioeconomic and environmental sustainability of banking institutions in Brazil using the Analytic Hierarchy Process with ratings approach

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