Modifications of the Limited Memory BFGS Algorithm for Large-scale Nonlinear Optimization [PDF]
, 2005 In this paper we present two new numerical methods for unconstrained large-scale optimization. These methods apply update formulae, which are derived by considering different techniques of approximating the objective function.
June, Leong Wah, Hassan, Malik Abu
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Benchmark of quantum-inspired heuristic solvers for quadratic unconstrained binary optimization
Scientific Reports, 2022 Recently, inspired by quantum annealing, many solvers specialized for unconstrained binary quadratic programming problems have been developed. For further improvement and application of these solvers, it is important to clarify the differences in their ...
Hiroki Oshiyama, Masayuki Ohzeki
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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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An Algorithm for Unconstrained Quadratically Penalized Convex Optimization [PDF]
Communications in Statistics - Simulation and Computation, 2011 A descent algorithm, "Quasi-Quadratic Minimization with Memory" (QQMM), is proposed for unconstrained minimization of the sum, $F$, of a non-negative convex function, $V$, and a quadratic form. Such problems come up in regularized estimation in machine learning and statistics. In addition to values of $F$, QQMM requires the (sub)gradient of $V$.
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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 ...
Mark W. Lewis +2 more
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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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On the Complexity of Local Search in Unconstrained Quadratic Binary Optimization [PDF]
SIAM Journal on Optimization, 2016 Minor update in 2016: simplified ...
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A modified quadratic hybridization of Polak-Ribiere-Polyak and Fletcher-Reeves conjugate gradient method for unconstrained optimization problems [PDF]
, 2017 This article presents a modified quadratic hybridization of the Polak–Ribiere–Polyak and Fletcher–Reeves conjugate gradient method for solving unconstrained optimization problems.
M.V. Thuto, Sindhu Narayanan, Pro Kaelo
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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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