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二层凸规划的基本性质 总被引:2,自引:0,他引:2
本文研究了一类抛述二层决策问题的二层数学规划模型,在一定条件下讨论了下层极值函数和上层复合目标函数的凸性和连续性,给出了二层决策问题优决策的存在条件。 相似文献
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二层广义凸规划及其性质 总被引:4,自引:0,他引:4
讨论了二层规划的性质 ,在一些凸性和广义凸性假设下 ,讨论了下层极值函数和上层目标函数的凸性、拟凸性和连续性性质 ,获得了五个定理 ,并予以证明 . 相似文献
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非可微二层凸规划的最优性条件 总被引:3,自引:0,他引:3
本文考虑的是构成函数为非可微凸函数的二层规划问题(NDBP),得到了下层极值函数和上层复合目标函数的方向导数和次微分的估计式,给出非可微二层凸规划(NDBP)最优解的几种最优性条件。 相似文献
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本文针对上层为凸的单目标、下层为线性多目标的二层规划问题提出了一个精确罚函数法,讨论了初始罚因子的选取,给出了精确罚因子及其自适应增加机制,并证明了该算法的有限终止性。 相似文献
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金照林 《数学的实践与认识》2023,(4):43-51
提出使用凸松弛的方法求解二层规划问题,通过对一般带有二次约束的二次规划问题的半定规划松弛的探讨,研究了使用半定规划(SDP)松弛结合传统的分枝定界法求解带有凸二次下层问题的二层二次规划问题,相比常用的线性松弛方法,半定规划松弛方法可快速缩小分枝节点的上下界间隙,从而比以往的分枝定界法能够更快地获得问题的全局最优解. 相似文献
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The zero duality gap that underpins the duality theory is one of the central ingredients in optimisation. In convex programming, it means that the optimal values of a given convex program and its associated dual program are equal. It allows, in particular, the development of efficient numerical schemes. However, the zero duality gap property does not always hold even for finite-dimensional problems and it frequently fails for problems with non-polyhedral constraints such as the ones in semidefinite programming problems. Over the years, various criteria have been developed ensuring zero duality gaps for convex programming problems. In the present work, we take a broader view of the zero duality gap property by allowing it to hold for each choice of linear perturbation of the objective function of the given problem. Globalising the property in this way permits us to obtain complete geometric dual characterisations of a stable zero duality gap in terms of epigraphs and conjugate functions. For convex semidefinite programs, we establish necessary and sufficient dual conditions for stable zero duality gaps, as well as for a universal zero duality gap in the sense that the zero duality gap property holds for each choice of constraint right-hand side and convex objective function. Zero duality gap results for second-order cone programming problems are also given. Our approach makes use of elegant conjugate analysis and Fenchel's duality. 相似文献
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In this paper, we introduce generalized essentially pseudoconvex function and generalized essentially quasiconvex function, and give sufficient optimality conditions of the nonsmooth generalized convex multi-objective programming and its saddle point theorem about cone efficient solution. We set up Mond-Weir type duality and Craven type duality for nonsmooth multiobjective programming with generalized essentially convex functions, and prove them. 相似文献
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Gert Wanka 《Journal of Mathematical Analysis and Applications》2002,275(1):354-368
In this paper we present a duality approach for a multiobjective fractional programming problem. The components of the vector objective function are particular ratios involving the square of a convex function and a positive concave function. Applying the Fenchel-Rockafellar duality theory for a scalar optimization problem associated to the multiobjective primal, a dual problem is derived. This scalar dual problem is formulated in terms of conjugate functions and its structure gives an idea about how to construct a multiobjective dual problem in a natural way. Weak and strong duality assertions are presented. 相似文献
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Computing exact solution to nonlinear integer programming: Convergent Lagrangian and objective level cut method 总被引:3,自引:0,他引:3
In this paper, we propose a convergent Lagrangian and objective level cut method for computing exact solution to two classes
of nonlinear integer programming problems: separable nonlinear integer programming and polynomial zero-one programming. The
method exposes an optimal solution to the convex hull of a revised perturbation function by successively reshaping or re-confining
the perturbation function. The objective level cut is used to eliminate the duality gap and thus to guarantee the convergence
of the Lagrangian method on a revised domain. Computational results are reported for a variety of nonlinear integer programming
problems and demonstrate that the proposed method is promising in solving medium-size nonlinear integer programming problems. 相似文献
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H. C. Lai J. C. Liu S. Schaible 《Journal of Optimization Theory and Applications》2008,137(1):171-184
We prove that a minmax fractional programming problem is equivalent to a minimax nonfractional parametric problem for a given
parameter in complex space. Using a parametric approach, we establish the Kuhn-Tucker type necessary optimality conditions
and prove the existence theorem of optimality for complex minimax fractional programming in the framework of generalized convexity.
Subsequently, we apply the optimality conditions to formulate a one-parameter dual problem and prove weak duality, strong
duality, and strict converse duality theorems involving generalized convex complex functions.
This research was partly supported by NSC, Taiwan. 相似文献
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Convex composite multi-objective nonsmooth programming 总被引:4,自引:0,他引:4
This paper examines nonsmooth constrained multi-objective optimization problems where the objective function and the constraints are compositions of convex functions, and locally Lipschitz and Gâteaux differentiable functions. Lagrangian necessary conditions, and new sufficient optimality conditions for efficient and properly efficient solutions are presented. Multi-objective duality results are given for convex composite problems which are not necessarily convex programming problems. Applications of the results to new and some special classes of nonlinear programming problems are discussed. A scalarization result and a characterization of the set of all properly efficient solutions for convex composite problems are also discussed under appropriate conditions.This research was partially supported by the Australian Research Council grant A68930162.This author wishes to acknowledge the financial support of the Australian Research Council. 相似文献
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This paper studies a class of multiobjective generalized fractional programming problems, where the numerators of objective functions are the sum of differentiable function and convex function, while the denominators are the difference of differentiable function and convex function. Under the assumption of Calmness Constraint Qualification the Kuhn-Tucker type necessary conditions for efficient solution are given, and the Kuhn-Tucker type sufficient conditions for efficient solution are presented under the assumptions of (F, α, ρ, d)-V-convexity. Subsequently, the optimality conditions for two kinds of duality models are formulated and duality theorems are proved. 相似文献
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For a kind of fractional programming problem that the objective functions are the ratio of two DC (difference of convex) functions with finitely many convex constraints, in this paper, its dual problems are constructed, weak and strong duality assertions are given, and some sufficient and necessary optimality conditions which characterize their optimal solutions are obtained. Some recently obtained Farkas-type results for fractional programming problems that the objective functions are the ratio of a convex function to a concave function with finitely many convex constraints are the special cases of the general results of this paper. 相似文献
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We show a Lagrange-type duality theorem for a DC programming problem, which is a generalization of previous results by J.-E. Martínez-Legaz, M. Volle [5] and Y. Fujiwara, D. Kuroiwa [1] when all constraint functions are real-valued. To the purpose, we decompose the DC programming problem into certain infinite convex programming problems. 相似文献
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Optimality Conditions and Duality for a Class of Nonlinear Fractional Programming Problems 总被引:25,自引:0,他引:25
Liang Z. A. Huang H. X. Pardalos P. M. 《Journal of Optimization Theory and Applications》2001,110(3):611-619
In this paper, we present sufficient optimality conditions and duality results for a class of nonlinear fractional programming problems. Our results are based on the properties of sublinear functionals and generalized convex functions. 相似文献