Multicriteria decision-making in flight route selection

2020 ◽  
Vol 92 (9) ◽  
pp. 1377-1384
Author(s):  
Leszek Rolka ◽  
Alicja Mieszkowicz-Rolka ◽  
Grzegorz Drupka

Purpose This paper aims to present a hybrid logical-arithmetic approach for selecting optimal flight routes. It can be used in the framework of free route airspace (FRA), which is aimed at achieving higher efficiency of air traffic management. Design/methodology/approach At the first stage, an initial subset of flight routes is selected that are promising alternatives with respect to single numerical criteria. At the second stage, a hybrid multicriteria decision model is constructed, consisting of numerical criteria and additional linguistic criteria. At the third stage, the numerical and linguistic criteria are integrated into a crisp decision matrix for determining the final ranking using the technique for order preferences by similarity to an ideal solution (TOPSIS) method. Findings The considered decision-making problem involves different kinds of criteria. Numerical (objective) criteria are given as real numbers. Linguistic (subjective) criteria are expressed with the help of fuzzy linguistic values. In consequence, a (logical) reasoning process prior to performing an (arithmetic) optimization procedure is necessary. Furthermore, a uniform optimization procedure requires a way of combining numerical and linguistic attributes. Practical implications The proposed approach can be applied to solving various multicriteria decision-making problems, where both objective and subjective criteria are taken into account. Originality/value First, a fuzzy information system that includes linguistic condition attributes is constructed. Second, a fuzzy inference system that is necessary for determining the resulting fuzzy criterion “turbulence conditions” for all flight routes is introduced. Finally, a way of combining numerical and linguistic criteria is proposed. This is done by converting values of fuzzy attributes into crisp ones, basing on the preferences of a decision-maker.

2020 ◽  
Vol 12 (5) ◽  
pp. 1707 ◽  
Author(s):  
Javier Puente ◽  
Isabel Fernandez ◽  
Alberto Gomez ◽  
Paolo Priore

This paper proposes the design of a conceptual model of quality assessment in European higher education institutions (HEIs) that takes into account some of the critical reflections made by certain authors in the literature regarding standards and guidelines suggested for this purpose by the European Higher Education Area (EHEA). In addition, the evaluation of the conceptual model was carried out by means of the reliable hybrid methodology MCDM-FIS (multicriteria decision making approach–fuzzy inference system) using FDEMATEL and FDANP methods (fuzzy decision-making trial and evaluation laboratory and FDEMATEL-based analytic network process). The choice of these methodologies was justified by the existing interrelationships among the criteria and dimensions of the model and the degree of subjectivity inherent in its evaluation processes. Finally, it is suggested to include sustainability as a determining factor in the university context due to its great relevance in the training of future professionals.


2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Fatma Dammak ◽  
Leila Baccour ◽  
Adel M. Alimi

This work is interested in showing the importance of possibility theory in multicriteria decision making (MCDM). Thus, we apply some possibility measures from literature to the MCDM method using interval-valued intuitionistic fuzzy sets (IVIFSs). These measures are applied to a decision matrix after being transformed with aggregation operators. The results are compared between each other and concluding remarks are drawn.


2020 ◽  
Vol 21 (6) ◽  
pp. 1707-1730
Author(s):  
Amir Karbassi Yazdi ◽  
Thomas Hanne ◽  
Juan Carlos Osorio Gómez

The aim of the study in this paper is to show how the performance of banks can be evaluated by ranking them based on Balanced Scorecard (BSC) and Multicriteria Decision Making (MCDM) methods. Nowadays, assessing the performance of companies is a vital work for finding their weaknesses and strengths. The banking sector is an important area in the service sector. Many people want to know which bank performs best when entrusting their money to them. For assessing the performance of banks, BSC can be used. This method helps to translate strategic issues to meaningful insights for the respective financial institutions. After that, the banks will be ranked based on performance indicators by the Weighted Aggregated Sum Product Assessment (WASPAS) method. Because this method is based on a decision matrix, weights are required. To find such weights, the Step-wise Weight Assessment Ratio Analysis (SWARA) method is applied. The results show that the International Bank of Colombia has a much better performance than other Colombian banks. Besides, further insights regarding the evaluation process based on BSC, SWARA, and WASPAS are obtained.


2020 ◽  
Vol 54 (4) ◽  
pp. 551-582
Author(s):  
Jolly Puri ◽  
Meenu Verma

PurposeThis paper is focused on developing an integrated algorithmic approach named as data envelopment analysis and multicriteria decision-making (DEA-MCDM) for ranking decision-making units (DMUs) based on cross-efficiency technique and subjective preference(s) of the decision maker.Design/methodology/approachSelf-evaluation in data envelopment analysis (DEA) lacks in discrimination power among DMUs. To fix this, a cross-efficiency technique has been introduced that ranks DMUs based on peer-evaluation. Different cross-efficiency formulations such as aggressive and benevolent and neutral are available in the literature. The existing ranking approaches fail to incorporate subjective preference of “one” or “some” or “all” or “most” of the cross-efficiency evaluation formulations. Therefore, the integrated framework in this paper, based on DEA and multicriteria decision-making (MCDM), aims to present a ranking approach to incorporate different cross-efficiency formulations as well as subjective preference(s) of decision maker.FindingsThe proposed approach has an advantage that each of the aggressive, benevolent and neutral cross-efficiency formulations contribute to select the best alternative among the DMUs in a MCDM problem. Ordered weighted averaging (OWA) aggregation is applied to aggregate final cross-efficiencies and to achieve complete ranking of the DMUs. This new approach is further illustrated and compared with existing MCDM approaches like simple additive weighting (SAW) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prove its validity in real situations.Research limitations/implicationsThe choice of cross-efficiency formulation(s) as per subjective preference of the decision maker and different orness levels lead to different aggregated scores and thus ranking of the DMUs accordingly. The proposed ranking approach is highly useful in real applications like R and D projects, flexible manufacturing systems, electricity distribution sector, banking industry, labor assignment and the economic environmental performances for ranking and benchmarking.Practical implicationsTo prove the practical applicability and robustness of the proposed integrated DEA-MCDM approach, it is applied to top twelve Indian banks in terms of three inputs and two outputs for the period 2018–2019. The findings of the study (1) ensure the impact of non-performing assets (NPAs) on the ranking of the selected banks and (2) are enormously valuable for the bank experts and policy makers to consider the impact of peer-evaluation and subjective preference(s) in formulating appropriate policies to improve performance and ranks of underperformed banks in competitive scenario.Originality/valueTo the best of the authors’ knowledge, this is the first study that has integrated both DEA and MCDM via OWA aggregation to present a ranking approach that can incorporate different cross-efficiency formulations and subjective preference(s) of the decision maker for ranking DMUs.


2019 ◽  
Vol 18 (2) ◽  
pp. 451-479 ◽  
Author(s):  
Olayinka Mohammed Olabanji ◽  
Khumbulani Mpofu

Purpose The purpose of this paper is to determine the suitability of adopting hybridized multicriteria decision-making models as a decision tool in engineering design. This decision tool will assist design engineers and manufacturers to determine a robust design concept before simulation and manufacturing while all the design features and sub features would have been identified during the decision-making process. Design/methodology/approach Fuzzy analytical hierarchy process (FAHP) and fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) are hybridized and applied to obtain optimal design of a reconfigurable assembly fixture (RAF) from a set of alternative design concepts. Design features and sub features associated with the RAF are identified and compared using fuzzified pairwise comparison matrices to obtain weights of their relative importance in the optimal design. The FAHP obtained the fuzzy synthetic extent (FSE) values of the design features and sub features. The FSE values are used as weights of the design features and sub features in generating the decision matrix. FTOPSIS and FTOPSIS based on left and right scores were adopted to predict effects of the weights. Results were obtained for normalized and unnormalized weights of the design features and its effects on the relative closeness coefficients of the design alternatives. Findings The improved performance of the FTOPSIS based on left and right scores is due to the involvement of the left and right scores of weights of the design features in the computation of distances from positive and negative ideal solutions. Embedding the weights of the design features in the normalized decision matrix before estimating the distances of the design concepts from ideal solutions reduces the dependency of the closeness coefficients on the weights of the design features. This also decreases the difference in the final values of the design concepts. In essence, the weights of the design features have an impact in the closeness coefficient. There is reduction in the closeness coefficients of the design concepts due to normalization of the weights of the design features. However, normalizing the weights of the design features did not affect the variations in the final values of the design concept. As the final value of the design concepts can be influenced by the normalized weights of the design features, it can be implied that normalization of weights of the sub features will also affect the decision matrix. The study has been able to proof that hybridizing FAHP and FTOPSIS can produce effective results for decisions on optimal design by the application of FTOPSIS based on left and right scores rather than the general FTOPSIS. Originality/value This research develops a hybridized multicriteria decision-making model for decision-making in engineering design. It presents a detailed extension of hybridized FAHP and FTOPSIS based on left and right scores as a useful tool for considering the relative importance of design features and sub features in optimal design selection.


2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Liguo Fei ◽  
Yong Hu ◽  
Fuyuan Xiao ◽  
Luyuan Chen ◽  
Yong Deng

Multicriteria decision-making (MCDM) is an important branch of operations research which composes multiple-criteria to make decision. TOPSIS is an effective method in handling MCDM problem, while there still exist some shortcomings about it. Upon facing the MCDM problem, various types of uncertainty are inevitable such as incompleteness, fuzziness, and imprecision result from the powerlessness of human beings subjective judgment. However, the TOPSIS method cannot adequately deal with these types of uncertainties. In this paper, aD-TOPSIS method is proposed for MCDM problem based on a new effective and feasible representation of uncertain information, calledDnumbers. TheD-TOPSIS method is an extension of the classical TOPSIS method. Within the proposed method,Dnumbers theory denotes the decision matrix given by experts considering the interrelation of multicriteria. An application about human resources selection, which essentially is a multicriteria decision-making problem, is conducted to demonstrate the effectiveness of the proposedD-TOPSIS method.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Luiz Carlos Magalhães Olimpio ◽  
Vanessa Ribeiro Campos ◽  
Esequiel Fernandes Teixeira Mesquita

PurposeThe study aims to identify and evaluate relevant criteria in the proposal and support of public administration policies for preventive maintenance comprised in a conservation approach to built heritage and aligned with local sustainable development of the historic center of the city of Sobral, in Brazil.Design/methodology/approachA novel multicriteria decision model adopting the Bayesian best-worst method is presented and its application and results are described. Though a systematic procedure, criteria were selected in order to protect the tangible and intangible values of cultural heritage, as well as its sustainable development. Then experts evaluate these criteria through an elicitation instrument.FindingsThe results show that for the decision problem over preventive maintenance, social contribution and historical record of built heritage are more important than its structural vulnerability, while architecture is less relevant. Due to the low restrictions, the subcriterion related to this property has the least influence. The weights can assist in the characterization of measures and policies for the protection of the built cultural heritage.Originality/valueThe use of a novel decision-making method in cultural heritage is an important initiative, given the frequent use of simple and inefficient methods. The identified and weighted criteria are important data to characterize the scenario and the topic. The results contribute to protection and development of the built heritage, encouraging the implementation of preventive conservation in the historic center, conferring to the public administration valuable information to support and propose initiatives.


2020 ◽  
Vol 12 (6) ◽  
pp. 2242 ◽  
Author(s):  
Alexei Pérez-Velázquez ◽  
Leandro Leysdian Oro-Carralero ◽  
Jorge Laureano Moya-Rodríguez

The necessary transformation of the world’s energy matrices has led to a growth in developing technologies based on renewable sources. In this context, photovoltaic panels and their components count in Brazil with a production and commercialization chain that has accumulated a sustained growth of more than 100% of its generation capacities between the years 2018 and 2019, and that can fulfill or overcome this rate in 2019 to 2020. However, the conditions of a competitive market and the availability of a significant number of middle and small companies for the distribution and installation of photovoltaic technology may represent a scenario where multiple indicators must be considered. The purpose of this study is to apply a combined method to aid decision-making that corresponds to the supplier selection of the technology in the context of Northeast Brazil. The method is composed by the combination of a diffuse inference technique together with a multicriteria decision-making method, VIKOR, and the weight assignment to the indicators using the entropy method, according to the values of the decision matrix resulting from the diffuse inference technique that allows to develop the calculus. The results show that data collection from multiple sources and based on input variables can offer metrics about the suppliers for the selection criteria. Restrictions derived from data collection can be a barrier, and the method relies on an adapted script that facilitates application.


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