Multicriteria Decision Aid Methods Research Articles

Improving the Decision-Making for Sustainable Demolition Waste Management by Combining a Building Information Modelling-Based Life Cycle Sustainability Assessment Framework and Hybrid Multi-Criteria Decision-Aiding Approach

Increasing efforts have been devoted to promoting sustainable demolition waste management (DWM) from a life cycle thinking perspective. To this end, facilitating sustainability-oriented decision-making for DWM planning requires a sustainability assessment framework for assessing the trade-offs among multifaceted criteria. This study develops a BIM-based DWM sustainability assessment approach to facilitate the life cycle sustainability assessment (LCSA) and decision-making by integrating LCSA-related properties and hybrid Multi-Criteria Decision-Aiding (MCDA) methods into a BIM environment using Dynamo visual scripting. A dynamic linkage is developed in the streamlined BIM-based LCSA process, where the enriched Industry Foundation Class (IFC) models are coupled with custom LCSA data templates to achieve seamless data exchange between the BIM platform and external LCA tools. Subsequently, hybrid MCDA methods convert the assessment results into DWM scenario ranking. A pilot study verifies the applicability of the BIM-based framework. The results unveil that the sustainability score ascended with the recycling rate. The optimal DWM alternative with the highest recycling rate yields the highest sustainability score at 91.63. Conversely, a DWM alternative reflecting the ‘status quo’ in China’s recycling industry has the lowest score at 8.37, significantly lower than the baseline scenario with a 50% recycling rate. It is worth noting that the ‘growth curve’ of the sustainability score continuously flattens as the target recycling rate escalates. The increment in recycling rate from the “Australian standard” scenario to the optimal scenario is 18.4%, whereas the sustainability score merely increases by 2.3%, implying that the former scenario arrived at an optimum point for maximising the cost-efficiency of DWM under the predefined settings.

On extension of 2-copulas for information fusion

Copulas are very applicable tools from a statistical point of view. Their capability to model joint distribution makes them a useful tool for statisticians. Yet, they have been applied rarely in multi-criteria decision aiding (MCDA). This paper introduces a novel family of aggregation functions based on 2-copulas for MCDA. More specifically, the proposed copula-based method is applied to construct the popular Choquet integral (CI) and attitudinal Choquet integral (ACI). The forms obtained are utilized to develop a machine learning model to explain choices in the human decision-making situations. Exemplary pairwise preferences are provided as training information for the proposed model. Our approach effectively represents the dependencies between criteria under uncertainty. Experimental results on multiple real-world datasets demonstrate that our approach significantly outperforms popular MCDA methods, such as RBF-kernel, Tchebycheff, etc.

Private Partner Prioritization for Public–Private Partnership Contracts in a Brazilian Water Company Using a Multi-Criteria Decision Aid Method

Public–private partnerships (PPPs) are long-term contracts between government entities and private companies, and are increasingly being adopted in developing countries due to the large need for investments in sectors such as water and sewerage and also in order to benefit from the experience and to have access to the resources and technology of the private sector. Prioritizing the private party of the contract becomes a complex decision due to the characteristics of PPP contracts, and a standard of evaluation has not been adopted yet, the decision usually being made by evaluating the price. Thus, this research aims to propose a set of criteria to be incorporated into the decision problem that involves technical aspects. It then seeks to rank alternatives by using a multi-criteria decision aid method, FITradeoff, which supports the decision-maker (DM) in prioritization and provides transparency and security to the process.

Single and Multiobjective Shutdown Optimization of a Multistage Continuous Crystallizer.

This study presents the first model-based optimal shutdown procedure of a multistage continuous crystallization process which aims at the maximization of on-spec production and minimization of the shutdown time. The cooling antisolvent crystallization of Aspirin (acetylsalicylic acid) in a three-stage continuous crystallizer was used as a case study. To address the optimal shutdown problem, several single optimization scenarios were considered to assess the impact of the degrees of freedom, discretization schemes, and optimization settings such as the constraints. The proposed optimal shutdown procedures showed that significant amounts of on-spec crystals can be produced both at fixed and variable shutdown times. Most importantly, the optimal shutdown procedures can match the steady-state productivity, based on the shutdown to steady-state productivity ratio (STSPR) which can easily reach 100%. Moreover, the residual shutdown material, considered as waste, can be dramatically reduced by >80% compared to the current standard shutdown procedures. Given the conflicting nature of the maximization of on-spec production and minimization of the shutdown time, multiobjective optimization of the shutdown operation was also addressed to identify the set of Pareto optimal solutions. Finally, a multicriteria decision-aiding method, based on multiattribute utility theory, was proposed to rank the Pareto optimal solutions to support the decision-making and help identify a suitable and feasible single optimal shutdown solution.

Valuation of Real Estate Investment Trusts using the PSI-CoCoSo Multicriteria Method

In recent years, we can observe the growth in the number of investors in the financial market. This work seeks to improve the decision-making process in real estate investment funds (Brazilian REITs). To this end, a literature review was carried out in the Scopus database using bibliometrix to analyze the applications of the multicriteria decision aid (MCDA) in the environment of Brazilian REITs, as a result, it was possible to analyze a greater approach to studies on the toma in Australia, the United Kingdom, the United States, and China. The study was promising because it opens new possibilities of approach and opportunities to cover applications, seeking to explore and use MCDA methods to provide support at all stages of the decision-making process. The literature review was used as a basis for structuring the problem and defining the application of the hybrid PSI-CoCoSo method for ordering Brazilian REITs in the corporate slabs sector traded on the São Paulo stock exchange (B3), the criterion was to address funds that have at least one million reais in daily trading on the stock exchange. As a result, the hybrid method proved to be effective in the ranking process, providing robust results on the application and evaluation of Brazilian REITs.

A multicriteria modeling approach for evaluating power generation scenarios under uncertainty: The case of green hydrogen in Greece

Clean energy technological innovations are widely acknowledged as a prerequisite to achieving ambitious long-term energy and climate targets. However, the optimal speed of their adoption has been parsimoniously studied in the literature. This study seeks to identify the optimal intensity of moving to a green hydrogen electricity sector in Greece, using the OSeMOSYS energy modeling framework. Green hydrogen policies are evaluated, first, on the basis of their robustness against uncertainty and, afterwards, against conflicting performance criteria and for different decision-making profiles towards risk, by applying the VIKOR and TOPSIS multi-criteria decision aid methods. Although our analysis focuses exclusively on the power sector and compares different rates of hydrogen penetration compared to a business-as-usual case without considering other game-changing innovations (such as other types of storage or carbon capture and storage), we find that a national transition to a green hydrogen economy can support Greece in potentially cutting at least 16 MtCO2 while stimulating investments of EUR 10–13 bn. over 2030–2050.

Selection of a Suitable Material by a Multi-Criteria Decision Aid Method (MCDM) for the Manufacture of the Buckets of a Micro Pelton Turbine

This article aims to investigate the effect of inertia on the outlet temperature of an evacuated tube solar collector. The experiments were conducted during a 24h period in Minquin County (latitude 38034’N, Longitude 10303’E). An analysis was made to determine whether the evacuated tube solar collectors’ fluid thermal inertia impacts the water storage tank temperature. The results showed differences between the useful energy delivered to the water storage tank in the case with mass flow rate adjusted depending on the incident solar radiation for the entire two days in which experiments were conducted. Two days of cloud and sunshine were considered. An indirect optimal control technique refers to the impacts of the inertia of water on the outlet collector temperature, the on/off control of the pump, and the useful heat gain from the storage tank. During days with clear sky, the average solar radiation, mass flow rate, outlet, and tank temperature were 640.02W/m2, 0.06kg/s, 290C, and 44.240C, respectively. For cloudy day was 449W/m2, 0.02kg/s, 270C and 420C respectively. The control system is provided to run the heating circulating pump after rest for several minutes to facilitate the exhaust system, then continues to run for a cycle. The DTP,ON and DTP, OFF range from 30C to 100C and from 0.20C to 1.50C, respectively.

Selection of a Suitable Material by a Multi-Criteria Decision Aid Method (Mcdm) for the Manufacture of the Buckets of a Micro Pelton Turbine

Micro hydro power plant remains a sustainable solution to meet the electrical needs of isolated populations when the potential is there. The discovery of new materials leads engineers to review the choice of material, in order to reduce the cost and facilitate the manufacture of hydromechanical components. In this study, to select the best choice of material for the manufacture of buckets of a micro Pelton turbine, we used multi-criteria decision support methods (MCDM) such as the Analytical Hierarchy Process (AHP), the order preference technique by similarity to the ideal solution (TOPSIS), the compromise solution (VIKOR). Based on of the literature review on the materials usable for the manufacture of hydraulic turbines, we were able to select five alternative materials such as mild steel ; aluminum alloy ; stainless steel ; high density polyethylene ; cast iron and seven very important material evaluation criteria for manufacturing such as machinability ; ultimate tensile strength ; the density ; hardness ; the cost ; maintenance cost and corrosion resistance. It appears from results via the AHP method that the coherence index of 0.0904 and the coherence ratio of 0.0669 are usable for the practice of material selection. Considering the performance scores for the five alternatives obtained via the TOPSIS and VIKOR techniques, it appears that high density polyethylene is the best material, followed by the aluminum alloy.

Comparison of multi-criteria decision aiding methods in the problem of employee recruitment

One of the most important categories of decisions made in the company are decisions regarding human resource management, in particular decisions related to the proper selection of personnel and recruitment. Wrong recruitment decisions can directly and indirectly lead to financial losses, while the right personnel selection decisions reduce job turnover, increase morale and eliminate the cost of subsequent recruitment process. The decision-making methods used in the literature in the recruitment of employees are mostly complicated, which may make their results unreliable for the management. Therefore, the article addresses the problem of verifying the applicability of relatively easy-to-use decision support methods, which were AHP (Analytic Hierarchy Process) and PROMETHEE (Preference Ranking Organization METHod for Enrichment Evaluations). Although in the considered problem of staff selection, the same candidate for employment was indicated as the best one, the conducted research allowed to conclude that these methods may lead to slightly different recommendations. Therefore, it is worth using both methods to confirm the results and obtain a more complete picture of possible decisions.

A FITRADEOFF-BASED APPROACH FOR STRATEGIC DECISIONS ON MILITARY BUDGET

This paper presents an actual application of the FITradeoff method to support strategic decisions on military budgets. Using Optimization Techniques and a particular Multicriteria Decision Aid method to assess budget allocation efficiency, a model was built for the Brazilian Defense Ministry. A case study of the Brazilian Navy is described in this paper, whereby this model was used. The focus is on the adaptations of FITradeoff necessary to make it suitable for different groups of decision-makers and staff, performing different tasks on the process. The FITradeoff proposal allowed a group decision with different levels suitable to the military context and high-level strategic decisions. The use of multicriteria in this approach provides a meaningful utility measure. This provides a score value representing the desirability of an alternative, in terms of its attainment of the institution’s strategic objectives. The approach contributed to an approximate gain of 15% in budget efficiency in 2022.

Feasibility Analysis of Biogas Production by Using GIS and Multicriteria Decision Aid Methods in the Central African Republic

Organic waste-derived biogas production is an effective way to transform biowaste into renewable energy for the electricity supply in developed and developing countries. This study analyzes the feasibility of biogas production as a solution to waste management and electricity supply in Bangui, the capital city of the Central African Republic. The selection of the biogas plant site in an urban area is a complex process due to the area availability and different factors. The GIS, combined with the MCDA, could analyze the environmental, social, and economic factors and criteria such as slope, settlement, rivers, land, urban growth, and local and major roads. Applying the ELECTRE TRI as the MCDA method enhanced the techniques to determine the suitable biogas plant site. The biowaste amount and distance from the suitable site were determined using the ArcGIS distance toolset. The biogas plant’s economic and environmental benefits, such as the electricity production capacity and CO2 reduction, were analyzed based on the population growth and the biogas production per year. The analyzed results obtain an area of 3.5 km2 for a large-scale biogas plant construction, with a potential production of 2,126,799.68 kW per year using combined heat and power and 2,303,100.23 kW by converting the thermal energy to electricity. This large-scale biogas plant could treat 20% of the organic waste per year, cover 60% of the city’s electricity demand, and reduce 946,200 kg of CO2 equivalent per year.

Prediction and optimization of gas distribution quality for high-temperature PEMFC based on data-driven surrogate model

Suitable operating conditions can improve the internal gas distribution of high-temperature proton exchange membrane fuel cell (HT-PEMFC), reduce the occurrence of local gas starvation, and thus prolong the lifespan. Therefore, it is important to investigate the gas distribution quality of HT-PEMFC based on quantitative indicators. In this paper, data-driven surrogate models are established based on the simulation results of a three-dimensional validated numerical model to study the gas distribution quality of HT-PEMFC via two qualitative evaluation indexes, the value of mean and standard deviation of the reactant gas concentration in catalyst layer. In order to obtain the surrogate model more efficiently and accurately, genetic algorithm optimized deep belief network (GA-DBN) and Autogluon (an automated machine learning method) are applied. Based on the surrogate models, the influence of the operating condition parameters on each evaluation index is revealed, which provides theoretical basis for the life-extension design of HT-PEMFC. Then, Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), a Multi-Criteria Decision Aid (MCDA) method, is used to select the optimal operating conditions according to the two evaluation indexes of gas distribution quality from the extensive computational results of the surrogate models, which provides specific guidance for the life duration improvement of HT-PEMFC.

A Systematic Review of the Applications of Multi-Criteria Decision Aid Methods (1977–2022)

Multicriteria methods have gained traction in academia and industry practices for effective decision-making. This systematic review investigates and presents an overview of multi-criteria approaches research conducted over forty-four years. The Web of Science (WoS) and Scopus databases were searched for papers on multi-criteria methods with titles, abstracts, keywords, and articles from January 1977 to 29 April 2022. Using the R Bibliometrix tool, the bibliographic data was evaluated. According to this bibliometric analysis, in 131 countries over the past forty-four years, 33,201 authors have written 23,494 documents on multi-criteria methods. This area’s scientific output increases by 14.18 percent every year. China has the highest percentage of publications at 18.50 percent, followed by India at 10.62 percent and Iran at 7.75 percent. Islamic Azad University has the most publications with 504, followed by Vilnius Gediminas Technical University with 456 and the National Institute of Technology with 336. Expert Systems with Applications, Sustainability, and the Journal of Cleaner Production are the top journals, accounting for over 4.67 percent of all indexed works. In addition, E. Zavadskas and J. Wang have the most papers in the multi-criteria approaches sector. AHP, followed by TOPSIS, VIKOR, PROMETHEE, and ANP, is the most popular multi-criteria decision-making method among the ten nations with the most publications in this field. The bibliometric literature review method enables researchers to investigate the multi-criteria research area in greater depth than the conventional literature review method. It allows a vast dataset of bibliographic records to be statistically and systematically evaluated, producing insightful insights. This bibliometric study is helpful because it provides an overview of the issue of multi-criteria techniques from the past forty-four years, allowing other academics to use this research as a starting point for their studies.

Uncertainty of Preferences in the Assessment of Supply Chain Management Systems Using the PROMETHEE Method

The use of Supply Chain Management (SCM) systems allows for the improvement of an organization’s operations. Companies use many Enterprise Resource Planning (ERP) systems that also include SCM functionalities. As a result, the selection of the right system to be used in the enterprise is a complex problem. The use of multi-criteria decision aid (MCDA) methods provides the possibility of system ordering in a ranking, based on an asymmetric preference relation, symmetric indifference and incomparability relations. The aim of the article is to evaluate ERP systems in terms of their support for SCM. The scientific contribution of the article is the study of the impact of various degrees of uncertainty of the decision-maker’s preferences on the evaluation results and the analysis of the impact of various approaches to the preferences of alternatives on the final ranking. An approach based on MCDA Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) was used for the study. The decision model uses 12 criteria, three different preference functions and two variants of the PROMETHEE method (I and II). In this way, a total of six rankings were built, and each of them includes seven systems, supporting the management of the supply chain. As a result of the study, it was found that the highest functionality in logistics is characterized by the Oracle E-Business Suite system, which is more functional than SAP ERP and JD Edwards EnterpriseOne. The remaining analysed systems offer much less functionality. The applied approach, which was possible with the use of various preference functions, allowed three different levels of uncertainty in the preferences of decision-makers to be taken into account in the study. Moreover, the application of two different variants of the PROMETHEE method made it possible for the obtained solution to take into account the uncertainty of positions taken by individual ERP systems in the final rankings.

A Multicriteria Decision Trading System Based on Prospect Theory: A Risk Return Analysis of the TODIM Method

This paper proposes a trading system (TS) based on a multicriteria decision aid (MCDA) process known as TODIM, (Multicriteria Interactive Decision Making) a Portuguese acronym for interactive and multicriteria decision-making. MCDA has been employed to solve financial questions because of its ability to deal with a complex environment populated with different sorts of criteria and alternatives, such as financial markets. The aim is to propose a general and adaptive tool for supporting the trading strategies of investors and market practitioners in such an environment. The reason for selecting TODIM among the different MCDA methods is that it is based on prospect theory, which assumes that the risk profile of the investor varies according to different situations, considering the risk of loss or gain. A list of simulations using some of the most prominent Brazilian stocks is performed, and the results are compared with the Buy-and-Hold benchmark and a TS based on an ensemble method for selecting trading rules. The results show that, compared to Buy-and-Hold, a TODIM-based TS provides the same level of return with a lower level of risk exposure. The consequence is superior risk adjustment parameters. As a result, we have a model with similar results in profit, but with superior results in relation to risk-based performance, which makes the method advantageous in relation to similar ones.

A hybrid AHPSort II and multi-objective portfolio selection method to support quality control in the automotive industry

There are several manufacturing errors of different criticality, severity, and occurrence. Correcting all of them is difficult and costly. In this paper, we propose a new hybrid approach to classifying manufacturing errors in an automotive plant and, consequently, to selecting the portfolio of processes that require more attention from the management of the company. Our approach consists of two steps. Firstly, we classify the errors in terms of priority, based on a set of criteria agreed with the management, using the multi-criteria decision-aiding method AHPSort II. The errors belonging to the highest priority class are the most urgent and critical for the company. Secondly, we define a multi-objective portfolio problem, selecting a set of the most critical processes based on the number of errors in each of these processes and on their priority. We adopted an interactive method for finding the most preferred portfolio of processes according to the stakeholder preferences. We applied this approach to a case study of the largest automotive company in Italy, Fiat Chrysler Automobiles, showing how classical quality control tools can benefit from the integration of multi-criteria decision-aiding techniques.

Strategic support for the distribution of vaccines against Covid-19 to Brazilian remote areas: A multicriteria approach in the light of the ELECTRE-MOr method

The pandemic caused by the new coronavirus has brought to light a series of concerns for the Brazilian population and government departments due to the different costly consequences that it has generated. It has also mobilized different strategic fronts that plan and implement several mitigating measures against the virus. Besides, the search for solutions for adequate care for individuals in need of support has been constant. This work uses ELECTRE-MOr, a Multi-Criteria Decision Aid (MCDA) method, to support the logistic plan for the vaccine distribution throughout Brazil, essentially to remote areas. The method allows an objective and structured classification of ideal types of thermal boxes for the storage of immunobiological inside the Cold Chain, presenting the best alternative that maintains the quality of materials until the final destination and has the best cost-benefit. Currently, the ELECTRE-MOr model is under development in a computational tool in Python, allowing the use of the method intuitively and clearly, enabling professionals of any area of expertise to apply it.

Multi-criteria analysis applied to humanitarian assistance: an approach based on ELECTRE-MOr

The recent increase in the number of cases of COVID-19 in Brazil and worldwide, caused by the Omicron Variant, has brought to light concern to the population and the government, especially in the states most affected by the pandemic. To find a way to help combat the pandemic, a case study was conducted to acquire new speedboats by the Brazilian Navy (BN), through the application of the ELECTRE-MOr multicriteria method. The boats would be employed as mobile hospitals, aiming to perform first aid and evacuation of patients from riverside regions to qualified hospitals. Another important use would be the transport of vaccines, medicines and basic supplies for riverside populations, such as water, food and hygiene materials. For the proposed analysis, we consulted three specialists from the BN, who evaluated eight boat models in seven tactical, operational and medical criteria. After the application of the method, the Guardian 25 and RAC boats were chosen to be employed in humanitarian assistance. This study brings a valuable contribution to academia and society since it represents the application of a multi-criteria decision-aid method in the state of the art to contribute to the solution of a real problem that affects millions of people in Brazil and worldwide.

Multicriteria Decision Aid Methods and portfolio selection: case study

This article focuses on some problems in finance that have a multi-criteria character, such as the prediction of bankruptcy, the credit risk and the constitution of the stock portfolio (the latter which will be the subject of a case study). Tunis Stock Exchange-), from this it evokes some existing studies in terms of solving the problems in finance by means of multi-criteria methods. From the point of view of the large number of criteria to be taken into consideration for the evaluation of titles, it is in this perspective that this article falls , devoted to the application of multicriteria methods in an attempt to evaluate shares with a view to constituting a portfolio of shares in the Tunisian stock market, the use of UTA + was intended to lead to a classification of actions according to their marginal utilities, this same classification has been refined thanks to the use of ELECTRE TRI.

Selection of Electric Vehicles for the Needs of Sustainable Transport under Conditions of Uncertainty—A Comparative Study on Fuzzy MCDA Methods

All over the world, including Poland, authorities are taking steps to increase consumer interest in electric vehicles and sustainable transport as a way to reduce environmental pollution. For this reason, the electric vehicle market is dynamically and constantly developing, more and more modern vehicles are introduced to it, and purchases are often subsidized by the government. The aim of the article is to analyse the A–C segments of the Polish electric vehicle market and to recommend the most attractive vehicle from the perspective of sustainable transport. The aim of the research was achieved with the use of three multi-criteria decision aid (MCDA) methods, which deal well with the uncertainty and imprecision of data that occur in the case of many different parameters of electric vehicles. In particular, the following methods were used: the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS), the fuzzy simple additive weighting (SAW) method, and the new easy approach to fuzzy preference ranking organization method for enrichment evaluation II (NEAT F-PROMETHEE II). Electric vehicle rankings obtained using each method were compared and verified by stochastic analysis. The conducted analyses and comparisons allowed us to identify the most interesting electric vehicles, which currently appear to be the Volkswagen ID.3 Pro S and Nissan LEAF e+.