Synergies between operations research and data mining: The emerging use of multi-objective approaches

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• 作者：David Corne^a ; ^{david.corne@gmail.com} ; Clarisse Dhaenens^b ; ^c ; ^{clarisse.dhaenens@lifl.fr} ; Laetitia Jourdan^b ; ^c ; ^{laetitia.jourdan@inria.fr}
• 关键词：State-of-the-art ; Operations research ; Knowledge-based systems ; Knowledge discovery ; Multi-objective optimization
• 刊名：European Journal of Operational Research
• 出版年：2012
• 期刊代码：58_03772217
• 类别：et
• 出版时间：16 September, 2012
• 卷：221
• 期：3
• 页码：469-479
• 文件大小：296 K

摘要

Operations research and data mining already have a long-established common history. Indeed, with the growing size of databases and the amount of data available, data mining has become crucial in modern science and industry. Data mining problems raise interesting challenges for several research domains, and in particular for operations research, as very large search spaces of solutions need to be explored. Hence, many operations research methods have been proposed to deal with such challenging problems. But the relationships between these two domains are not limited to these natural applications of operations research approaches. The counterpart is also important to consider, since data mining approaches have also been applied to improve operations research techniques. The aim of this article is to highlight the interplay between these two research disciplines. A particular emphasis will be placed on the emerging theme of applying multi-objective approaches in this context.