Bounds for Binary Integer Programming via Unconstrained Quadratic Pseudo-Boolean Optimization
MathematicsThis research proposes a method for finding bounds in binary integer programming (BIP) and quadratic binary integer programming (QBIP). Our approach utilizes a max-flow technique within the framework of quadratic pseudo-Boolean optimization.
Sirilak Phonin, Chulin Likasiri
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A New Augmented Lagrangian Method for Equality Constrained Optimization with Simple Unconstrained Subproblem [PDF]
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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An Improved Adaptive Trust-Region Method for Unconstrained Optimization [PDF]
Mathematical Modelling and Analysis, 2014 In this study, we propose a trust-region-based procedure to solve unconstrained optimization problems that take advantage of the nonmonotone technique to introduce an efficient adaptive radius strategy.
Hamid Esmaeili, Morteza Kimiaei
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Quantum ReportsThe optimization of investment portfolios represents a pivotal task within the field of financial economics. Its objective is to identify asset combinations that meet specified criteria for return and risk.
Mirko Mattesi +6 more
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Unconstrained formulation of standard quadratic optimization problems [PDF]
, 2012 A standard quadratic optimization problem (StQP) consists of finding the largest or smallest value of a (possibly indefinite) quadratic form over the standard simplex which is the intersection of a hyperplane with the positive orthant.
PALAGI, Laura +2 more
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HUBO formulations for solving the eigenvalue problem
Results in Control and Optimization, 2023 Solving the eigenvalue problem is particularly important in almost all fields of science and engineering. With the development of quantum computers, multiple algorithms have been proposed for this purpose.
Kyungtaek Jun, Hyunju Lee
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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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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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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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