arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1609.08082cs.NEcs.AI

An Ontology of Preference-Based Multiobjective Metaheuristics

National University of Defense Technology(国防科技大学);Leiden University(莱顿大学);De Montfort University(德蒙福特大学);Instituto Universitário de Lisboa (ISCTE-IUL)(里斯本大学学院);Polytechnic Institute of Leiria(莱里亚理工学院);University of Münster(明斯特大学)

Longmei Li, Iryna Yevseyeva, Vitor Basto-Fernandes, Heike Trautmann, Ning Jing, Michael Emmerich

英文摘要:

User preference integration is of great importance in multi-objective optimization, in particular in many objective optimization. Preferences have long been considered in traditional multicriteria decision making (MCDM) which is based on mathematical programming. Recently, it is integrated in multi-objective metaheuristics (MOMH), resulting in focus on preferred parts of the Pareto front instead of the whole Pareto front. The number of publications on preference-based multi-objective metaheuristics has increased rapidly over the past decades. There already exist various preference handling methods and MOMH methods, which have been combined in diverse ways. This article proposes to use the Web Ontology Language (OWL) to model and systematize the results developed in this field. A review of the existing work is provided, based on which an ontology is built and instantiated with state-of-the-art results. The OWL ontology is made public and open to future extension. Moreover, the usage of the ontology is exemplified for different use-cases, including querying for methods that match an engineering application, bibliometric analysis, checking existence of combinations of preference models and MOMH techniques, and discovering opportunities for new research and open research questions.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑