Analysis and selection of Enterprise Architecture (EA) scenarios is a difficult and complex decision making process directly effecting the long-term business strategies realization. This complexity is associated with ...
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Analysis and selection of Enterprise Architecture (EA) scenarios is a difficult and complex decision making process directly effecting the long-term business strategies realization. This complexity is associated with contradictory objectives and significant uncertainties involved in analysis process. Although a large body of intuitive and analytical models for EA analysis has evolved over the last few years, none of them leads to an efficient and optimized ranking in fuzzy environments. Moreover, it is necessary to simultaneously employ some complementary methods to reflect the ambiguity and vagueness as the main sources of uncertainty. This paper incorporates the concept of Data Envelopment Analysis (DEA) model into EA scenario analysis through a group analysis under uncertain conditions. To resolve the vagueness and ambiguity of the EA analysis, fuzzy credibility constrained programming and p-robustness technique are applied, respectively. Not only is the proposed DEA model linear, robust, and flexible in aggregating experts' opinion in a group decision making process, but it also is successful in discrimination power improvement - a major shortcoming associated with classic DEA model. The proposed model provides useful solutions to support decision making process for large-scale Information Technology (IT) development planning. (C) 2015 Elsevier B.V. All rights reserved.
Eutrophication is a global problem for coastal ecosystems, one that Bohai Bay, China, has been severely afflicted due to rapid economic and social development in the past decades. It was urgent to manage the total max...
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Eutrophication is a global problem for coastal ecosystems, one that Bohai Bay, China, has been severely afflicted due to rapid economic and social development in the past decades. It was urgent to manage the total maximum allocated loads (TMALs) of the total nitrogen (TN) and total phosphorus (TP) on land-based, which was closely related to coastal eutrophication. In this study, from the perspective of economy-resources-environment (ERE) system, we presented the fuzzycredibilityconstrained linear programming based on pressure-state-response (PSR-FCCLP) model, which calculated the TMALs of TN and TP at three credibility levels (lambda = 0.55, 0.75, and 0.95) in Bohai Bay. The results showed that when the credibility level increased from 0.55 to 0.95, the TMALs of TN and TP would decrease from 13,573.38 t/a to 12,820.00 t/a and from 2665.58 t/a to 2514.90 t/a, respectively. This study will provide support for environmental management in coastal regions.
In this study, a fuzzy credibility constrained programming (FCCP) model is developed for water quantity and quality management with uncertainties in water quality parameters. The proposed method could reflect not only...
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In this study, a fuzzy credibility constrained programming (FCCP) model is developed for water quantity and quality management with uncertainties in water quality parameters. The proposed method could reflect not only inexact uncertainties in the objective function, variables and parameters, but also fuzzy uncertainties in the right-hand side. credibility levels which represent satisfaction degrees of the constraints can be analysed. The developed model is applied to a case study of water resources management within one river basin, three subareas and three water users regarding water environment security. According to the different confidence levels and sewage recovery, scenario analysis is conducted to analyse possible events in water allocation and water quality control. The resulting solutions obtained show that the proposed method can help decision-makers to provide scientific bases for water quantity and quality management and energy system planning, solid waste management and other environmental system problems.
In this paper, an interval two-stage fuzzycredibility constraint programming (ITSFCCP) method is proposed to deal with multiple uncertainties that can be expressed as fuzzy sets, discrete intervals and probability di...
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In this paper, an interval two-stage fuzzycredibility constraint programming (ITSFCCP) method is proposed to deal with multiple uncertainties that can be expressed as fuzzy sets, discrete intervals and probability distributions, which can be used for effectively reflect natural and social complexities of relevant decision-making processes. Lincang city of Yunnan province, which is located in the southwest border of China, is employed as the demonstrative case. It is a frontier window and an important channel for China to face the "radiation center" of Southeast and South Asia. Also, it is the intersection of the Tropic of Cancer and the Geographic Water Distribution Line between the Pacific and Indian Oceans. The city's water resources system is particularly unique due to its connection with Myanmar. Considering multiple uncertainties and complexities of the existing water resources system in the city, ITSFCCP is developed to optimize the allocation of water resources. The objective function of the model is the maximization of economic benefits of the water resources system. fuzzy sets, discrete intervals and probability distribution were introduced to represent the multiple uncertainties associated with the natural and social complexities. credibility levels were adopted to solve the complexity of multi-ethnic human society in Lincang. The results showed that the model could effectively deal with the uncertainties and complexities of Lincang's water resources system, and reflect the trade-offs between the system benefits and risks.
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