Discrete Dynamics in Nature and Society, 2017 We propose a new method for equality constrained optimization based on augmented Lagrangian method. We construct an unconstrained subproblem by adding an adaptive quadratic term to the quadratic model of augmented Lagrangian function.
Hao Zhang, Qin Ni
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Robust optimisation of unconstrained binary quadratic problems
International Journal of Operational Research, 2019 In this paper we focus on the unconstrained binary quadratic optimization model, maximize x^t Qx, x binary, and consider the problem of identifying optimal solutions that are robust with respect to perturbations in the Q matrix.. We are motivated to find robust, or stable, solutions because of the uncertainty inherent in the big data origins of Q and ...
Lewis, Mark +2 more
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A Modified Class of Conjugate Gradient Algorithms Based on Quadratic Model for Nonlinear Unconstrained Optimization [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2014 In this paper, we have investigated a new class of conjugate gradient algorithms for unconstrained non-linear optimization which are based on the quadratic model. Some theoretical results are investigated which are sufficient descent and ensure the local
Basim Hassan, Hameed Sadiq
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A novel hybrid backtracking search optimization algorithm for continuous function optimization [PDF]
Decision Science Letters, 2019 Stochastic optimization algorithm provides a robust and efficient approach for solving complex real world problems. Backtracking Search Optimization Algorithm (BSA) is a new stochastic evolutionary algorithm and the aim of this paper is to introduce a ...
Sukanta Nama, Apu Kumar Saha
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Quantum Algorithms for Mixed Binary Optimization Applied to Transaction Settlement
IEEE Transactions on Quantum Engineering, 2021 In this article, we extend variational quantum optimization algorithms for quadratic unconstrained binary optimization problems to the class of mixed binary optimization problems.
Lee Braine +3 more
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On global minimizers of quadratic functions with cubic regularization [PDF]
, 2018 In this paper, we analyze some theoretical properties of the problem of minimizing a quadratic function with a cubic regularization term, arising in many methods for unconstrained and constrained optimization that have been proposed in the last years ...
Cristofari, Andrea +2 more
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A New Spectral Conjugate Gradient method for solving unconstrained Optimization problems [PDF]
مجلة ابحاث كلية التربية الاساسية, 2022 The spectral conjugate gradient methods are fascinating, and it has been shown that they are useful for strictly convex quadratic reduction when used properly.
أسامة محمد طاهر ویس +2 more
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Approach to development of algorithms of Newtonian methods of unconstrained optimization, their software implementation and benchmarking [PDF]
Компьютерные исследования и моделирование, 2013 The approach to increase efficiency of Gill and Murray's algorithm of Newtonian methods of unconstrained optimization with step adjustment creation is offered, rests on Choleskys factorization.
Gennadiy Anatolievich Zelenkov +1 more
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Exploiting Hardware and Software Advances for Quadratic Models of Wind Farm Layout Optimization
IEEE Access, 2022 A key aspect of the design of a wind farm is the wind farm layout optimization (WFLO) problem: given a wind farm site and information about the wind patterns, the problem is to decide the location of individual wind turbines to maximize energy production
Arik Senderovich +3 more
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Geometric approach to Fletcher's ideal penalty function [PDF]
, 1995 Original article can be found at: www.springerlink.com Copyright Springer. [Originally produced as UH Technical Report 280, 1993]In this note, we derive a geometric formulation of an ideal penalty function for equality constrained problems.
Christianson, B.
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