Logistic regression for criteria weight elicitation in PROMETHEE-based ranking methods

For a PROMETHEE II method used to rank concurrent alternatives both preference functions and weights are required, and if the weights are unknown, they can be elicited by leveraging present or past partial rankings. If the known partial ranking is incorrect, the eliciting methods are ineffective. In this paper a logistic regression method for weight elicitation is proposed to tackle this scenario. An experiment is carried out to compare the logistic regression method performance against a state-of-the-art linear weight elicitation method, proving the validity of the proposed methodology

Indoor Environmental Quality (IEQ): A Comparison between TOPSIS- and PROMETHEE-Based Approaches for Indirect Eliciting of Category Weights

Indoor Environmental Quality (IEQ) has received a great deal of attention in recent years due to the relationship between worker comfort and productivity. Many academics have studied IEQ from both a building design and an IEQ assessment perspective. This latter line of research has mostly used direct eliciting to obtain weights assigned to IEQ categories such as thermal comfort, visual comfort, acoustic comfort, and indoor air quality. We found only one application of indirect eliciting in the literature. Such indirect eliciting operates without the need for imprecise direct weighing and requires only comfort evaluations, which is in line with the Industry 5.0 paradigm of individual, dynamic, and integrated IEQ evaluation. In this paper, we use a case study to compare the only indirect eliciting model already applied to IEQ, based on TOPSIS, to an indirect eliciting method based on PROMETHEE and to a classical direct eliciting method (AHP). The results demonstrate the superiority of indirect eliciting in reconstructing individual preferences related to perceived global comfort

Synergetic Application of Multi-Criteria Decision-Making Models to Credit Granting Decision Problems

Although various algorithms have widely been studied for bankruptcy and credit risk prediction, conclusions regarding the best performing method are divergent when using different performance assessment metrics. As a solution to this problem, the present paper suggests the employment of two well-known multiple-criteria decision-making (MCDM) techniques by integrating their preference scores, which can constitute a valuable tool for decision-makers and analysts to choose the prediction model(s) more properly. Thus, selection of the most suitable algorithm will be designed as an MCDM problem that consists of a finite number of performance metrics (criteria) and a finite number of classifiers (alternatives). An experimental study will be performed to provide a more comprehensive assessment regarding the behavior of ten classifiers over credit data evaluated with seven different measures, whereas the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE) techniques will be applied to rank the classifiers. The results demonstrate that evaluating the performance with a unique measure may lead to wrong conclusions, while the MCDM methods may give rise to a more consistent analysis. Furthermore, the use of MCDM methods allows the analysts to weight the significance of each performance metric based on the intrinsic characteristics of a given credit granting decision problem

EmC-ICDSST 2019: 5th International Conference on Decision Support System Technology - ICDSST 2019 & EURO Mini Conference 2019 on "Decision Support Systems: Main Developments & Future Trends"

info:eu-repo/semantics/publishedVersio

Typology Selection of Retaining Walls Based on Multicriteria Decision-Making Methods

This research received no external funding.In civil engineering and construction, in the selection of the most adequate and sustainable alternative, all of the alternatives and selection criteria, such as the requirements of the construction process (which are often overlooked) and the preferences of designers, clients, or contractors, are not always taken into account. The purpose of this article is to suggest a methodology that may allow studying all of the possible alternatives to find the most ideal solution among all of the existing possibilities for the selection of retaining walls to be built in infrastructures in different environments. For this purpose, all typologies of retaining walls and selection criteria (external requirements, construction requirements, characteristics of the natural land and economic criteria) are first identified. Subsequently, a simple methodological method is proposed, allowing the relative importance of each criterion to be established and allowing us to select the most suitable solution for each situation by successively applying different multicriteria decision-making methods. Finally, the methodology developed is applied to two projects in different locations with different constraints. The results obtained provide a set of compromise solutions that remain as best-rank alternatives when the weights of the criteria change. Therefore, the methodology developed can be applied to the selection of typologies of other structures in future projects

A novel standardized assessment for the new end uses of recycled water schemes

University of Technology, Sydney. Faculty of Engineering and Information Technology.Nowadays, recycled water has provided sufficient flexibility to satisfy short-term freshwater needs and increase the reliability of long-term water supplies in many water scarce areas. It becomes an essential component of integrated water resources management. However, the current applications of recycled water are still quite limited with non-potable purposes such as irrigation, industrial uses, toilet flushing, car washing and environmental flows. There is a potential to exploit and develop new end uses of recycled water in both urban and rural areas. This can contribute largely to freshwater savings, wastewater reduction and water sustainability. This thesis put forwards a conceptual decision making framework for the systematic feasibility assessment of sustainable water management strategies in related to new end uses of recycled water’s planning, establishment and implementation. Due to the transparency, objectivity and comprehensiveness, the analytic framework can facilitate the optional management strategy selection process within a larger context of the community, processes, and models in recycled water decision-making. Based on that, a simplified quantitative Multi-criteria Analysis (MCA) was conducted in Rouse Hill Development Area (RHDA), Sydney, Australia, using the Multi-attribute Utility Theory (MAUT) technique. The results indicated that recycled water for a household laundry was the optimum solution which best satisfied the overall evaluation criteria. Another two management options can be excluded from further consideration in initial stages, namely the implementation of Level 1 water restriction on the use of recycled water and recycled water for swimming pools. With the identified strengths of recycled water use in washing machines, five relevant management alternatives were proposed according to different recycled water treatment technologies such as microfiltration (MF), granular activated carbon (GAC) or reverse osmosis (RO), and types of washing machines (WMs). Accordingly, a comprehensive quantitative assessment on the trade-off among a variety of issues (e.g., technical, risk, social, environmental and economic aspects) was performed over the alternatives. Overall, the MF treated recycled water coupled with new washing machines and the MF-GAC treated recycled water coupled with existing washing machines were shown to be preferred options. The results could provide a powerful guidance for sustainable water reuse in the long term. However, more detailed field trials and investigations are still needed to understand, predict and manage the impact of selected recycled water new end use alternatives effectively. Notably, public acceptability becomes important to ensure the successful development of recycled water new application in household laundries. This thesis addresses social issues by extensive social attitude surveys conducted in three locations of Australia, namely Port Macquarie, Melbourne and Sydney. Based on responses from Port Macquarie and Melbourne, the regression models provide conclusions about which characteristics are more likely to lead to the acceptance of recycled water from society. Three attitudinal variables (i.e., recycled water is an alternative to drinking water, attitude and cost) and three psychological variables (i.e., odour, reading and a small treatment unit) were found to be the key driving forces behind domestic water reuse behaviour. Comparatively, survey results in Sydney indicated slightly different aspects of concern. Due to experience in current use on dual pipe systems, Sydney residents interviewed have established good cognitions on the appearance and cost of recycled water. They were more concerned about the colour of clothes and potential damage to washing machines. The overall findings could drive future research to achieve a better public perception of the new end uses of recycled water. Moreover, the thesis also demonstrates the feasibility and cost-effectiveness of applying a zeolite filtration column as an effective ion-exchange resin for recycled water softening prior to use in washing machines. At the laboratory scale, the column service life for a typical washing machine was approximately one month without material regeneration on the basis of an optimal contact time (i.e., 5 minutes) and the calculated breakthrough capacity (i.e., 14 milligram hardness ions per gram of zeolites). It is believed that with a full application at households, this unit is likely to play a positive role in guaranteeing the recycled water quality as well as changing the public perception on the safe use of recycled water

The sustainable management of land and fisheries resources using multicriteria techniques: A meta-analysis

In recent years modern societies have attached a multifunctional requirement to the use of renewable resources, making their optimal sustainable management more complex. In the last decades, in many cases, this complexity is addressed by formulating management models with the help of the concepts and methods belonging to the well-known multicriteria decision-making (MCDM) paradigm. The purpose of this paper was to undertake a hermeneutic meta-analysis of the literature provided in primary journals on issues related to the management of these resources with the help of the MCDM paradigm. In this way, the paper aimed to obtain new, basic insights with considerations that might improve the efficiency of future research in the field studied. The meta-analysis was implemented by formulating and testing a battery of hypotheses of how the MCDM methods have been used in the past for the formulation of management models for the type of resource analyzed.The work of Carlos Romero, Carlos Iglesias-Merchan, and Luis Diaz-Balteiro was funded by the Ministry of Economy and Competitiveness of Spain under project AGL2015-68657-R. Additionally, this research was partially financed by the European Union’s H2020 Research and Innovation Programme under the Marie Sklodowska-Curie Actions, grant agreement No. 691149–SuFoRun

Inducing a probability distribution in Stochastic Multicriteria Acceptability Analysis

In multiple criteria decision aiding, very often the alternatives are compared by means of a value function compatible with the preferences expressed by the Decision Maker. The problem is that, in general, there is a plurality of compatible value functions, and providing a final recommendation on the problem at hand considering only one of them could be considered arbitrary to some extent. For such a reason, Stochastic Multicriteria Acceptability Analysis gives information in statistical terms by taking into account a sample of models compatible with the provided preferences. These statistics are given assuming the existence of a probability distribution in the space of value functions being defined a priori. In this paper, we propose some methods aiming to build a probability distribution on the space of value functions considering the preference information given by the Decision Maker. To prove the goodness of our proposal we performed an extensive set of simulations. Moreover, a sensitivity analysis on the variables of our procedure has been done as well