南京理工大学学报（自然科学版）2011，Vol.35Issue(2)：245-251,7.
一种基于模糊逻辑引入偏好信息的多目标遗传算法
Multi-objective Optimization Genetic Algorithm Incorporating Preference Information Based on Fuzzy Logic
摘要
Abstract
In order to solve the difficulty for users to select from many non-dominated solutions in multi-objective optimization, a multi-objective genetic algorithm incorporating preference information of the decision maker interactively is proposed. The algorithm makes use of a new nine-scale evaluation method to convert the linguistic preferences expressed by the decision maker to importance factors of objectives. A new outranking relation called "strength superior" which is based on the preference information is constructed via a fuzzy inference system to compare individuals instead of the commonly used "Pareto dominance" relation. The computational complexity of the algorithm is analyzed theoretically, and its ability to handle preference information is validated through simulation. Comparisons to two classical multi-objective genetic algorithms indicate that the proposed algorithm can search better solutions.关键词
模糊逻辑/多目标优化/遗传算法/偏好Key words
fuzzy logic/ multi-objective optimization/ genetic algorithm/ preference分类
信息技术与安全科学引用本文复制引用
申晓宁,李涛,张敏..一种基于模糊逻辑引入偏好信息的多目标遗传算法[J].南京理工大学学报（自然科学版）,2011,35(2):245-251,7.基金项目
空间智能控制技术国家级重点实验室资助项目 （）
江苏省高校自然科学研究计划项目(10KJB510010) （10KJB510010）
南京信息工程大学科研基金 （）
