(p, r)-ρ-(η, θ)- invinvity下不可微极大极小比约束问题的充分最优性条件和对偶性

Q4 Engineering
N. Kailey, Sonali Sethi, Shivani Saini
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引用次数: 0

摘要

有几类决策问题会显式或隐式地提示分式规划问题。投资组合问题、农业规划、信息传递、随机过程的数值分析和资源分配问题只是其中的几个例子。极大极小分式规划问题的大量应用激发了我们对这个主题的研究。研究一类不可微极小极大分式规划问题。研究了与原问题相对应的参数对偶模型,并给出了该问题最优解的充分最优性条件。进一步,我们得到了在(p, r)-ρ-(η, θ)-invexity假设下的各种对偶结果。此外,我们还确定了一个函数只存在于(- 1,1)-ρ-(η, θ)-凸函数类中,而不存在于文献中已有的(1,−1)-凸函数和(1,−1)-凸函数类中。本文给出了一类不可微极大极小问题的非平凡模型,并利用本文导出的最优性结果得到了该问题的最优解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sufficient optimality condition and duality of nondifferentiable minimax ratio constraint problems under (p, r)-ρ-(η, θ)-invexity
Abstract There are several classes of decision-making problems that explicitly or implicitly prompt fractional programming problems. Portfolio selection problems, agricultural planning, information transfer, numerical analysis of stochastic processes, and resource allocation problems are just a few examples. The huge number of applications of minimax fractional programming problems inspired us to work on this topic. This paper is concerned with a nondifferentiable minimax fractional programming problem. We study a parametric dual model, corresponding to the primal problem, and derive the sufficient optimality condition for an optimal solution to the considered problem. Further, we obtain the various duality results under (p, r)-ρ-(η, θ)-invexity assumptions. Also, we identify a function lying exclusively in the class of (−1, 1)-ρ-(η, θ)-invex functions but not in the class of (1, −1)-invex functions and convex function already existing in the literature. We have given a non-trivial model of nondifferentiable minimax problem and obtained its optimal solution using optimality results derived in this paper.
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来源期刊
Control and Cybernetics
Control and Cybernetics 工程技术-计算机:控制论
CiteScore
0.50
自引率
0.00%
发文量
0
期刊介绍: The field of interest covers general concepts, theories, methods and techniques associated with analysis, modelling, control and management in various systems (e.g. technological, economic, ecological, social). The journal is particularly interested in results in the following areas of research: Systems and control theory: general systems theory, optimal cotrol, optimization theory, data analysis, learning, artificial intelligence, modelling & identification, game theory, multicriteria optimisation, decision and negotiation methods, soft approaches: stochastic and fuzzy methods, computer science,
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