Multicriteria decision making under conditions of uncertainty in application to multiobjective allocation of resources

Ramalho, Felipe Diniz; Ekel, Petr; Pedrycz, Witold; Júnior, Joel Gomes Pereira; Soares, Gustavo Luís

doi:10.1016/j.inffus.2018.12.010

Cited by 35 publications

(57 citation statements)

References 28 publications

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“…In order to incorporate the preferences of different experts E i e i ..., , 1 ,  , related to the levels of importance attributed to each spatial criterion, the models [3] for considering qualitative information in the multiobjective analysis are adapted for multiattribute spatial decision problems. Besides, different experts involved in the decision process may have their own perceptions of the problem.…”

Section: Evaluation Of Spatial Criteria According To Preferences Omentioning

confidence: 99%

“…The correct definition of weights is important to reflect the preferences of the DMs. So, in order to do this, we adapt the techniques for including information of qualitative character in multiobjective models, proposed in [3] and, more recently, discussed in [4]. These techniques permit one to reflect the importance levels of the criteria for the multiattribute spatial problems in accordance with opinions of different DMs.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, the main contribution of this work is the development of the methodological tools to consider qualitative information in solving spatial problems with their particular application to the determination of generating sites for REGSs. The main innovative factor is the adaptation and improvement of the models [3] that permits one to consider the question of quantifying the levels of relative importance of the spatial criteria, considering that these levels may be quite different for different DMs. The preferences are transformed and processed within the framework of the AHP.…”

Section: Introductionmentioning

confidence: 99%

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Multiattribute Spatial Decision-Making for Qualitative Information Processing as Applied to the Renewable Energy Generating Sites Prospection

Silva

Ekel

Vieira³

et al. 2020

IEEE Access

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The objective of this research is to develop methodological tools to consider qualitative information in solving spatial problems with their particular application to the determination of generating sites for renewable energy systems. This locational problem has a complex nature and its solution has to be capable to take into account a wide range of considerations, as well as evaluations of a qualitative character. In this sense, the proposed process of elaborating decisions starts with studies related to the spatial criteria, which are modeled and processed within the Spatial Multicriteria Analysis. The relative importance of the spatial criteria is established by the involved experts on the basis of the construction, transformation, and processing of preference relations within the framework of the Analytic Hierarchy Process. The resulting decision maps are generated by aggregating the spatial criteria, applying the Ordered Weighted Averaging operator and the linguistic quantifiers. These maps permit one to highlight rational solution alternatives, which, if necessary, are evaluated, compared, chosen, prioritized, and/or ordered, applying additional spatial criteria (of quantitative as well as qualitative character), by means of techniques for preference modeling in a fuzzy environment (within the framework of so-called   R X , models). The corresponding decision process permits one to take into account and process quantitative and qualitative spatial criteria as well as preferences and judgments of the experts. The paper results are illustrated by a Case Study related to the determination of the most suitable locational alternatives for renewable power plants in the Minas Gerais state, Brazil.

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Section: Evaluation Of Spatial Criteria According To Preferences Omentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Multiattribute Spatial Decision-Making for Qualitative Information Processing as Applied to the Renewable Energy Generating Sites Prospection

Silva

Ekel

Vieira³

et al. 2020

IEEE Access

Self Cite

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“…Therefore, when the resource base of an enterprise is weak, there are many limitations to the decisions made by managers [59,60], and the managers are reluctant to take risks [61]. In such cases, companies often adopt more conservative innovation strategies, such as exploitation.…”

Section: Hypothesis 1b (H1b)mentioning

confidence: 99%

The Formation and Effects of Exploitative Dynamic Capabilities and Explorative Dynamic Capabilities: An Empirical Study

Liu

2019

Sustainability

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Although previous studies have explored the formation and effects of dynamic capabilities, much remains to be learned on this topic. There has been little research on the formation and effects of exploitative dynamic capabilities and explorative dynamic capabilities. This paper provides an explanation of how entrepreneurial leadership style and slack resources affect the formation of exploitive dynamic capabilities and explorative dynamic capabilities and evaluates the effects of exploitive dynamic capabilities and explorative dynamic capabilities on competitive advantage. Based on a sample of 382 Chinese firms, the empirical results show that a transactional leadership style and absorbed slack resources can encourage the formation of exploitative dynamic capabilities, and that a transformational leadership style and unabsorbed slack resources are conducive to the development of explorative dynamic capabilities. Furthermore, exploitative dynamic capabilities and explorative dynamic capabilities can reinforce and complement each other. Exploitative dynamic capabilities positively impact explorative dynamic capabilities, and explorative dynamic capabilities enhance exploitative dynamic capabilities. In particular, exploitative dynamic capabilities have an important effect on short-term financial performance, and explorative dynamic capabilities lead to a significant long-term competitive advantage. The results show that explorative dynamic capabilities surpass exploitative dynamic capabilities in terms of competitive advantage, even if both have a positive influence on competitive advantage. This study validates and develops the theory of dynamic capabilities.

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“…A identificação multiobjetivo de sistemas não consiste a apenas encontrar o conjunto Pareto-Ótimo mas também escolher dentro deste conjunto qual modelo utilizar, sendo o estágio de decisão uma parte crucial de qualquer otimização multiobjetivo. Diversos trabalhos da literatura endereçam a atenção para o problema de decisão, Aguirre et al (2006) apresenta um método de validação de modelos não lineares queé utilizado em (Barbosa, 2010) como critério decisor em uma metodologia de Identificação Multiobjetivo, Barroso et al (2007) propõe um critério de decisão baseado na mínima correlação entre o erro de simulação livre e a saída do modelo, a decisão multiobjetivoé utilizada no problema de alocação de recursos em (Ramalho et al, 2019). Estes procedimentos tem por objetivo selecionar apenas um modelo dentro do conjunto Pareto-Ótimo que melhor se adéqueàs necessidades segundo algum critério.…”

Section: Introductionunclassified

Rede Combinatória de Modelos Não Lineares - Parte I: Método e Aplicação em Identificação Multiobjetivo de Sistemas

Andrade

Martins

2019

Anais Do 14º Simpósio Brasileiro De Automação Inteligente

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This work is an part of a series of two articles and proposes a combinatorial network of nonlinear models. The method proposes an analytical form of parallel model combining and an algorithm for calculating weights for each model is provided. The method is applied from submodels pertaining to the Pareto-Set obtained through a multiobjective procedure for selecting nonlinear structures. The composite model obtained better performance than the submodels used in the validation indexes analyzed, reaching a reduction of 65% in the NRMSE index, 95% in the MSE index of the static curve, 87% in the energy of the vector of residues and a reduction of 21% in the autocorrelation energy of the vector of residues. Resumo: Este trabalhoé parte integrante de uma série de dois artigos e propõe uma rede combinatória de modelos não lineares. O método traz uma forma analítica de combinar modelos paralelamente e um algoritmo para o cálculo dos pesos que ponderam os modelosé fornecido. A técnicaé aplicada a partir de submodelos pertencentes ao conjunto Pareto-Ótimo obtidos através de um procedimento multiobjetivo de seleção de estruturas de modelos não lineares. O modelo composto obteve melhor desempenho que os submodelos utilizados em sua obtenção noś ındices de validação analisados, obtendo uma redução de 65% noíndice NRMSE, 95% noíndice MSE da curva estática, 87% na energia do vetor de resíduos e uma redução de 21% na energia da autocorrelação do vetor de resíduos.

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Multicriteria decision making under conditions of uncertainty in application to multiobjective allocation of resources

Cited by 35 publications

References 28 publications

Multiattribute Spatial Decision-Making for Qualitative Information Processing as Applied to the Renewable Energy Generating Sites Prospection

Multiattribute Spatial Decision-Making for Qualitative Information Processing as Applied to the Renewable Energy Generating Sites Prospection

The Formation and Effects of Exploitative Dynamic Capabilities and Explorative Dynamic Capabilities: An Empirical Study

Rede Combinatória de Modelos Não Lineares - Parte I: Método e Aplicação em Identificação Multiobjetivo de Sistemas

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