A Framework of Business Intelligence System for Decision Making in Efficiency Management

被引:7
作者
Borissova, Daniela [1 ,2 ]
Cvetkova, Petya [1 ]
Garvanov, Ivan [1 ]
Garvanova, Magdalena [1 ]
机构
[1] Univ Lib Studies & Informat Technol, Sofia 1784, Bulgaria
[2] Bulgarian Acad Sci, Inst Informat & Commun Technol, Sofia 1113, Bulgaria
来源
COMPUTER INFORMATION SYSTEMS AND INDUSTRIAL MANAGEMENT, CISIM 2020 | 2020年 / 12133卷
关键词
Business intelligence; Decision support framework; MCDA; MCDM; Optimization models; ENERGY EFFICIENCY;
D O I
10.1007/978-3-030-47679-3_10
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The business decisions at different levels require processing different kinds of information. In this regard, the usage of suitable tools will contribute to making effective business decisions. The described framework of the business intelligence system aims to support such decisions in an effective way. The core of the proposed decision support system relies on several modules with a different database. One of them contains the input data of the particular problem, second include multi-criteria design analysis models, while the next contains optimization models to support decision-making. These optimization models are the focus of the current article. Two single and one multi-objective optimization models are formulated to express different situations and to support business decisions via reasonable solutions. Depending on the particular purpose, one of the models can be used to determine the best or compromise decision, which contributes to the effectiveness in business management. The applicability of the proposed models and respectively the core of the framework of business decision-making in efficiency management is illustrated in public street lights renovation. The obtained results show that all models are practically applicable in the determination of corresponding decisions in accordance with the selected goal. As the essences of the proposed framework are the optimization models this proves the effectiveness of optimization models in decision making to support efficient management.
引用
收藏
页码:111 / 121
页数:11
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