Yue Ruan^{1, *}, Samuel Marsh², Xilin Xue¹, Zhihao Liu³, Jingbo Wang^{2, *}

CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1237-1247, 2020, DOI:10.32604/cmc.2020.010001

Abstract The Quantum Approximate Optimization Algorithm (QAOA) is an algorithmic framework for finding approximate solutions to combinatorial optimization problems. It consists of interleaved unitary transformations induced by two operators labelled the mixing and problem Hamiltonians. To fit this framework, one needs to transform the original problem into a suitable form and embed it into these two Hamiltonians. In this paper, for the well-known NP-hard Traveling Salesman Problem (TSP), we encode its constraints into the mixing Hamiltonian rather than the conventional approach of adding penalty terms to the problem Hamiltonian. Moreover, we map edges (routes) connecting each pair of cities to qubits,… More >

Chung-Lun Kuo, Chein-Shan Liu, Jiang-Ren Chang

The International Conference on Computational & Experimental Engineering and Sciences, Vol.19, No.2, pp. 35-36, 2011, DOI:10.3970/icces.2011.019.035

Abstract In this study, the exponentially convergent scalar homotopy algorithm (ECSHA) is proposed to solve the nonlinear optimization problems under equality and inequality constraints. The Kuhn-Tucker optimality conditions associated with NCP-functions are adopted to transform the nonlinear optimization problems into a set of nonlinear algebraic equations. Then the ECSHA is used to solve the resultant nonlinear equations. The proposed scheme keeps the merit of the conventional homotopy method, such as global convergence, but the inverse of the Jacobian matrix is avoid with the aid of the scalar homotopy function. Several numerical examples are provided to demonstrate the efficiency of the proposed… More >

H.F. Chan, C.M. Fan

The International Conference on Computational & Experimental Engineering and Sciences, Vol.19, No.1, pp. 29-30, 2011, DOI:10.3970/icces.2011.019.029

Abstract The inverse boundary optimization problem, which is governed by Helmholtz equation, is analyzed by the modified collocation Trefftz method (MCTM) and the exponentially convergent scalar homotopy algorithm (ECSHA). In the inverse boundary optimization problem, the position for part of boundary with given boundary condition is unknown, and the position for the rest of boundary with additionally specified boundary conditions is given. Therefore, it is very difficult to handle the boundary optimization problem by any numerical scheme. In order to stably solve the boundary optimization problem, the MCTM, one kind of boundary-type meshless methods, will be adopted in this study, since… More >

Chein-Shan Liu¹, Satya N. Atluri²

CMES-Computer Modeling in Engineering & Sciences, Vol.34, No.2, pp. 155-178, 2008, DOI:10.3970/cmes.2008.034.155

Abstract In this paper we propose a novel method for solving a nonlinear optimization problem (NOP) under multiple equality and inequality constraints. The Kuhn-Tucker optimality conditions are used to transform the NOP into a mixed complementarity problem (MCP). With the aid of (nonlinear complementarity problem) NCP-functions a set of nonlinear algebraic equations is obtained. Then we develop a fictitious time integration method to solve these nonlinear equations. Several numerical examples of optimization problems, the inverse Cauchy problems and plasticity equations are used to demonstrate that the FTIM is highly efficient to calculate the NOPs and MCPs. The present method has some… More >

Hsin-Fang Chan¹, Chia-Ming Fan^1,2, Weichung Yeih¹

CMC-Computers, Materials & Continua, Vol.24, No.2, pp. 125-142, 2011, DOI:10.3970/cmc.2011.024.125

Abstract The inverse boundary optimization problem, governed by the Helmholtz equation, is analyzed by the Trefftz method (TM) and the exponentially convergent scalar homotopy algorithm (ECSHA). In the inverse boundary optimization problem, the position for part of boundary with given boundary condition is unknown, and the position for the rest of boundary with additionally specified boundary conditions is given. Therefore, it is very difficult to handle the boundary optimization problem by any numerical scheme. In order to stably solve the boundary optimization problem, the TM, one kind of boundary-type meshless methods, is adopted in this study, since it can avoid the… More >