具有支持函数的非光滑半无限E-凸多目标规划的最优性和对偶性

Q3 Mathematics International Journal for Simulation and Multidisciplinary Design Optimization Pub Date : 2020-01-11 DOI:10.1051/smdo/2020011

Tarek Emam

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引用次数: 1

摘要

本文研究了一个包含支持函数的非光滑半无限多目标E-凸规划问题。我们得到了原始问题的充分最优性条件。我们为原始问题建立了Mond-Weir型对偶，并在各种广义E-凸性假设下建立了弱对偶和强对偶定理。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Optimality and duality for nonsmooth semi-infinite E-convex multi-objective programming with support functions

In this paper, we study a nonsmooth semi-infinite multi-objective E-convex programming problem involving support functions. We derive sufficient optimality conditions for the primal problem. We formulate Mond-Weir type dual for the primal problem and establish weak and strong duality theorems under various generalized E-convexity assumptions.

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来源期刊

International Journal for Simulation and Multidisciplinary Design Optimization Mathematics-Control and Optimization

CiteScore

2.00

自引率

0.00%

发文量

审稿时长

16 weeks

期刊介绍： The International Journal for Simulation and Multidisciplinary Design Optimization is a peer-reviewed journal covering all aspects related to the simulation and multidisciplinary design optimization. It is devoted to publish original work related to advanced design methodologies, theoretical approaches, contemporary computers and their applications to different fields such as engineering software/hardware developments, science, computing techniques, aerospace, automobile, aeronautic, business, management, manufacturing,... etc. Front-edge research topics related to topology optimization, composite material design, numerical simulation of manufacturing process, advanced optimization algorithms, industrial applications of optimization methods are highly suggested. The scope includes, but is not limited to original research contributions, reviews in the following topics: Parameter identification & Surface Response (all aspects of characterization and modeling of materials and structural behaviors, Artificial Neural Network, Parametric Programming, approximation methods,…etc.) Optimization Strategies (optimization methods that involve heuristic or Mathematics approaches, Control Theory, Linear & Nonlinear Programming, Stochastic Programming, Discrete & Dynamic Programming, Operational Research, Algorithms in Optimization based on nature behaviors,….etc.) Structural Optimization (sizing, shape and topology optimizations with or without external constraints for materials and structures) Dynamic and Vibration (cover modelling and simulation for dynamic and vibration analysis, shape and topology optimizations with or without external constraints for materials and structures) Industrial Applications (Applications Related to Optimization, Modelling for Engineering applications are very welcome. Authors should underline the technological, numerical or integration of the mentioned scopes.).