Identification of a Multicriteria Decision-Making Model Using the Characteristic Objects Method

Piegat, Andrzej; Sałabun, Wojciech

doi:10.1155/2014/536492

Cited by 43 publications

(16 citation statements)

References 56 publications

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“…In previous works, the accuracy of the COMET method was verified [43]. The formal notation of the COMET method should be briefly recalled [46,47,49]:…”

Section: The Comet Methodsmentioning

confidence: 99%

A New Approach to Identifying a Multi-Criteria Decision Model Based on Stochastic Optimization Techniques

Kizielewicz

Sałabun

2020

Symmetry

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Many scientific papers are devoted to solving multi-criteria problems. Researchers solve these problems, usually using methods that find discrete solutions and with the collaboration of domain experts. In both symmetrical and asymmetrical problems, the challenge is when new decision-making variants emerge. Unfortunately, discreet identification of preferences makes it impossible to determine the preferences for new alternatives. In this work, we propose a new approach to identifying a multi-criteria decision model to address this challenge. Our proposal is based on stochastic optimization techniques and the characteristic objects method (COMET). An extensive work comparing the use of hill-climbing, simulated annealing, and particle swarm optimization algorithms are presented in this paper. The paper also contains preliminary studies on initial conditions. Finally, our approach has been demonstrated using a simple numerical example.

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“…In previous works, the accuracy of the COMET method was verified [43]. The formal notation of the COMET method should be briefly recalled [46,47,49]:…”

Section: The Comet Methodsmentioning

confidence: 99%

A New Approach to Identifying a Multi-Criteria Decision Model Based on Stochastic Optimization Techniques

Kizielewicz

Sałabun

2020

Symmetry

Self Cite

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“…The basic concept of COMET method was proposed by prof. Piegat [26,27]. The formal notation of COMET method is presented in the five following steps [27,30,31,32].…”

Section: Characteristic Objects Methodsmentioning

confidence: 99%

Comparative Analysis of MCDM Methods for Assessing the Severity of Chronic Liver Disease

Piegat

Sałabun

2015

Lecture Notes in Computer Science

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Abstract. The paper presents the Characteristic Objects method as a potential multi-criteria decision-making method for use in medical issues. The proposed approach is compared with TOPSIS and AHP. For this purpose, assessment of the severity of Chronic Liver Disease (CLD) is used. The simulation experiment is presented on the basis of the Model For End-Stage Liver Disease (MELD). The United Network for Organ Sharing (UNOS) and Eurotransplant use MELD for prioritizing allocation of liver transplants. MELD is calculated from creatinine, bilirubin and international normalized ratio of the prothrombin time (INR). The correctness of the selection is examined among randomly selected one million pairs of patients. The result is expressed as a percentage of agreement between the assessed method and MELD selection. The Characteristic Objects method is completely free of the rank reversal phenomenon, obtained by using the set of characteristic objects. In this approach, the assessment of each alternative is obtained on the basis of the distance from characteristic objects and their values. As a result, correctness of the selection obtained by using the Characteristic Objects method is higher than those obtained by TOPSIS or AHP techniques.

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“…Therefore, in order to unify the standard and eliminate the dimensional impact, data normalization is the key link in the sustainable development evaluation. The most common normalization methods in MCDA methods include the minimum-maximum method, the vector method, the sum method, the maximum method, and the minimum method [25][26][27]. However, in much of the literature, there is no clear assignment to which decisionmakers' methods of data normalization are used.…”

Section: Introductionmentioning

confidence: 99%

Economic, Social, and Ecological Impact Evaluation of Traffic Network in Beijing–Tianjin–Hebei Urban Agglomeration Based on the Entropy Weight TOPSIS Method

Zhang

Yuan³

et al. 2021

Sustainability

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In recent years, with the rapid development of urban transportation network in China, many problems have been exposed, especially in the Beijing–Tianjin–Hebei (BTH) region. Under the call of sustainable development, it is of great significance to evaluate the economic, social, and ecological (ESE) impact of transportation network in BTH urban agglomeration for promoting the sustainable development of transportation ESE in BTH urban agglomeration. In this paper, 12 indicators in the field of transportation are selected to build the evaluation index system of ESE effects of transportation network in BTH urban agglomeration. By using entropy weight TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) model and the Jenks natural breaks classification method, the ESE impacts of transportation network in 13 cities of BTH from 2013 to 2017 are analyzed from the temporal and spatial dimensions. The research shows that: (1) From 2013 to 2017, the economic impact degree of traffic network shows an annual fluctuation trend, the social impact degree increases year by year, and the ecological impact degree decreases year by year; (2) For the cities of BTH, the ESE impact assessment results of transportation network from 2013 to 2017 can be divided into seven clusters. Except Handan City, the ESE impact assessment categories of other cities’ transportation network have been improved, but the proportion of cities in the transition period is still large, especially the “Low-Low-Low” cities. The types of cities in the transitional period need to be focused. It is still a heavy burden to realize the ESE coordination and sustainable development of BTH urban agglomeration transportation network.

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Identification of a Multicriteria Decision-Making Model Using the Characteristic Objects Method

Cited by 43 publications

References 56 publications

A New Approach to Identifying a Multi-Criteria Decision Model Based on Stochastic Optimization Techniques

A New Approach to Identifying a Multi-Criteria Decision Model Based on Stochastic Optimization Techniques

Comparative Analysis of MCDM Methods for Assessing the Severity of Chronic Liver Disease

Economic, Social, and Ecological Impact Evaluation of Traffic Network in Beijing–Tianjin–Hebei Urban Agglomeration Based on the Entropy Weight TOPSIS Method

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