A neurodynamic approach for a class of pseudoconvex semivectorial bilevel optimization problems

IF 1.4 3区 数学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Optimization Methods & Software Pub Date : 2024-08-14 DOI:10.1080/10556788.2024.2380688
Tran Ngoc Thang, Dao Minh Hoang, Nguyen Viet Dung
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Abstract

The article proposes an exact approach to finding the global solution of a nonconvex semivectorial bilevel optimization problem, where the objective functions at each level are pseudoconvex, and th...
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一类伪凸半矢量双层优化问题的神经动力学方法
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来源期刊
Optimization Methods & Software
Optimization Methods & Software 工程技术-计算机:软件工程
CiteScore
4.50
自引率
0.00%
发文量
40
审稿时长
7 months
期刊介绍: Optimization Methods and Software publishes refereed papers on the latest developments in the theory and realization of optimization methods, with particular emphasis on the interface between software development and algorithm design. Topics include: Theory, implementation and performance evaluation of algorithms and computer codes for linear, nonlinear, discrete, stochastic optimization and optimal control. This includes in particular conic, semi-definite, mixed integer, network, non-smooth, multi-objective and global optimization by deterministic or nondeterministic algorithms. Algorithms and software for complementarity, variational inequalities and equilibrium problems, and also for solving inverse problems, systems of nonlinear equations and the numerical study of parameter dependent operators. Various aspects of efficient and user-friendly implementations: e.g. automatic differentiation, massively parallel optimization, distributed computing, on-line algorithms, error sensitivity and validity analysis, problem scaling, stopping criteria and symbolic numeric interfaces. Theoretical studies with clear potential for applications and successful applications of specially adapted optimization methods and software to fields like engineering, machine learning, data mining, economics, finance, biology, or medicine. These submissions should not consist solely of the straightforward use of standard optimization techniques.
期刊最新文献
Superlinear convergence of an interior point algorithm on linear semi-definite feasibility problems Automatic source code generation for deterministic global optimization with parallel architectures A neurodynamic approach for a class of pseudoconvex semivectorial bilevel optimization problems An investigation of stochastic trust-region based algorithms for finite-sum minimization A trust-region scheme for constrained multi-objective optimization problems with superlinear convergence property
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