摘要
研究了含有不确定信息的多目标半无限分式优化问题,并借助一种新定义的向量运算关系,将鲁棒对应模型转化为一般的多目标优化问题,给出两者之间的关系。通过鲁棒型次微分约束规格以及广义凸函数,研究不确定多目标半无限分式规划的最优性条件,并研究了相应的混合型对偶。研究结果主要将有关半无限分式规划的最优性必要条件进行改进,并在新定义的type-I函数条件下研究了充分条件。
The multi-objective semi-infinite fractional optimization problem with uncertain information is studied.The robust correspondence model is transformed into a general multi-objective optimization problem by means of a newly defined vector arithmetic relation,and the relationship between the two is presented.The optimality condi⁃tions for uncertain multi-objective semi-infinite fractional programming are studied through the robust subdif⁃ferential constraint specifications and generalized convex functions,and the corresponding mixed duality is also studied.The results of the study mainly improve the necessary optimality conditions for semi-infinite fractional programming and study the sufficient conditions under the new defined type-I function condition.
作者
吕涵融
李向有
LV Hanrong;LI Xiangyou(College of Mathematics and Computer Science,Yan’an University,Yan’an 716000,China)
出处
《延安大学学报(自然科学版)》
2025年第1期65-72,共8页
Journal of Yan'an University:Natural Science Edition
基金
国家自然科学基金项目(11961072)。
关键词
多目标分式规划
拟Pareto弱有效解
广义凸性
混合型对偶
multi-objective fractional programming
quasi Pareto weakly efficient solutions
generalized convexity
mixed type duality
