Results 11 to 20 of about 34,499 (189)
An adaptive, multivariate partitioning algorithm for global optimization of nonconvex programs [PDF]
Journal of Global Optimization, 2019 In this work, we develop an adaptive, multivariate partitioning algorithm for solving mixed-integer nonlinear programs (MINLP) with multi-linear terms to global optimality. This iterative algorithm primarily exploits the advantages of piecewise polyhedral relaxation approaches via disjunctive formulations to solve MINLPs to global optimality in ...
Harsha Nagarajan +4 more
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Energy Reports, 2021 Hydropower is one of the significant renewable energy resources. It is regularly requested at peak time steps to meet the load requirements of power systems resources allocation. Therefore, modeling the optimal operation of hydropower systems to maximize
Yin Fang +5 more
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Energies, 2023 The design of an efficient energy management system (EMS) for monopolar DC networks with high penetration of photovoltaic generation plants is addressed in this research through a convex optimization point of view.
Oscar Danilo Montoya +2 more
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Economic dispatch in power system networks including renewable energy resources using various optimization techniques [PDF]
Archives of Electrical Engineering, 2021 Economic dispatch (ED) is an essential part of any power system network. ED is howto schedule the real power outputs from the available generators to get the minimum cost while satisfying all constraints of the network.
Abrar Mohamed Hafiz +2 more
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Global solutions of nonconvex standard quadratic programs via mixed integer linear programming reformulations [PDF]
Journal of Global Optimization, 2018 A standard quadratic program is an optimization problem that consists of minimizing a (nonconvex) quadratic form over the unit simplex. We focus on reformulating a standard quadratic program as a mixed integer linear programming problem.
J. Gondzio, E. Yıldırım
semanticscholar +1 more source
An ADMM-based SQP method for separably smooth nonconvex optimization
Journal of Inequalities and Applications, 2020 This work is about a splitting approach for solving separably smooth nonconvex linearly constrained optimization problems. Based on the ideas from two classical methods, namely the sequential quadratic programming (SQP) and the alternating direction ...
Meixing Liu, Jinbao Jian
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Deterministic global optimization with Gaussian processes embedded [PDF]
Mathematical Programming Computation, 2020 Gaussian processes (Kriging) are interpolating data-driven models that are frequently applied in various disciplines. Often, Gaussian processes are trained on datasets and are subsequently embedded as surrogate models in optimization problems.
Artur M. Schweidtmann +6 more
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Branch-and-bound performance estimation programming: a unified methodology for constructing optimal optimization methods [PDF]
Mathematical programming, 2022 We present the Branch-and-Bound Performance Estimation Programming (BnB-PEP), a unified methodology for constructing optimal first-order methods for convex and nonconvex optimization.
Shuvomoy Das Gupta +2 more
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BMC Bioinformatics, 2012 Background The estimation of parameter values for mathematical models of biological systems is an optimization problem that is particularly challenging due to the nonlinearities involved.
Miró Anton +4 more
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Systems Science & Control Engineering, 2020 We propose a new two-level vertex-searching algorithm framework that finds a global optimal solution to the continuous bilevel linear fractional programming problem over a compact polyhedron, in which both the upper and the lower objectives are linear ...
Hui-Ju Chen
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