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Quantum computing-enhanced topology optimization with stress constraints for truss structures 认领 引用 被引量：2
1
作者 Yan Wang Dixiong Yang +1 位作者 Zhenzeng Lei Guohai Chen 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第6期41-57,共17页
Quantum computing,leveraging the properties of quantum physics such as quantum superposition and entanglement,possesses the potential for exponential acceleration compared to classical computing.It can significantly e... Quantum computing,leveraging the properties of quantum physics such as quantum superposition and entanglement,possesses the potential for exponential acceleration compared to classical computing.It can significantly enhance solution efficiency in topology optimization and effectively avoid the entrapment in local optima.This paper proposes a hybrid classical-quantum computing framework to solve the stress-constrained topology optimization problem for truss structures.Initially,structural analyses are performed on a classical computer to determine the stresses of truss members.Then,the optimization problem is formulated through incremental updates of member cross-sectional areas to make it compatible with a quantum annealer.The update strategy consists of a directional-control function and a magnitude-control function.By embedding stress constraints directly into the directional-control function,the original optimization problem is reformulated as a quadratic unconstrained binary optimization model suitable for quantum annealing.To realize a balance between solution accuracy and iteration efficiency,a dynamic strategy for adjusting the magnitude of area increments is proposed.Thus,the quantum annealer can effectively achieve the optimal solutions.When only the access time of the quantum processing unit is considered,the results from 2D and 3D examples of truss topology optimization validate the effectiveness of the proposed framework,and demonstrate the great potential of quantum computing in structural optimization. 展开更多
关键词 Topology optimization Truss structures Quantum computing Quantum annealing algorithm Quadratic unconstrained binary optimization problem
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A NEW NONMONOTONE TRUST REGION ALGORITHM FOR SOLVING UNCONSTRAINED OPTIMIZATION PROBLEMS 认领 引用
2
作者 Jinghui Liu Changfeng Ma 《Journal of Computational Mathematics》 SCIE CSCD 2014年第4期476-490,共15页
Based on the nonmonotone line search technique proposed by Gu and Mo(Appl.Math.Comput.55,(2008)pp.2158-2172),a new nonmonotone trust region algorithm is proposed for solving unconstrained optimization problems in this... Based on the nonmonotone line search technique proposed by Gu and Mo(Appl.Math.Comput.55,(2008)pp.2158-2172),a new nonmonotone trust region algorithm is proposed for solving unconstrained optimization problems in this paper.The new algorithm is developed by resetting the ratioρk for evaluating the trial step dk whenever acceptable.The global and superlinear convergence of the algorithm are proved under suitable conditions.Numerical results show that the new algorithm is effective for solving unconstrained optimization problems. 展开更多
关键词 Unconstrained optimization problems Nonmonotone trust region method Global convergence Superlinear convergence.
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An Inexact Halley's Method 认领 引用
3
作者 YAN Gui-feng TIAN Xiang 《Journal of Beijing Institute of Technology》 EI CAS 2005年第3期340-343,共4页
An inexact Halley's method-Halley-PCG(preconditioned conjugate gradient)method is proposed for solving the systems of linear equations for improved Halley method either by Cholesky factorization exactly or by prec... An inexact Halley's method-Halley-PCG(preconditioned conjugate gradient)method is proposed for solving the systems of linear equations for improved Halley method either by Cholesky factorization exactly or by preconditioned conjugate gradient method approximately.The convergence result is given and the efficiency of the method compared to the improved Halley's method is shown. 展开更多
关键词 unconstrained optimization problems improved Halley's method preconditioned conjugate gradient method
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