Paradox 发表于 2025-3-26 22:49:08
A surperlinearly convergent algorithm for constrained optimization problems, incorporates a rule for choosing the penalty parameter and, near a solution, employs a search are rather than a search direction to avoid truncation of the step length, and thereby loss of superlinear convergence.使熄灭 发表于 2025-3-27 03:13:09
http://reply.papertrans.cn/16/1533/153214/153214_32.png小教堂 发表于 2025-3-27 08:17:21
On some experiments which delimit the utility of nonlinear programming methods for engineering desif algorithms was studied. The variable parameters included the number of design variables, the number of inequality constraints, the number of equality constraints and the degree of nonlinearity of the objective function and constraints. Also a combined penalty function and linear approximation algorithm was investigated.notice 发表于 2025-3-27 13:14:32
http://reply.papertrans.cn/16/1533/153214/153214_34.pnggrowth-factor 发表于 2025-3-27 13:39:34
https://doi.org/10.1007/978-3-658-24698-3f algorithms was studied. The variable parameters included the number of design variables, the number of inequality constraints, the number of equality constraints and the degree of nonlinearity of the objective function and constraints. Also a combined penalty function and linear approximation algorithm was investigated.面包屑 发表于 2025-3-27 18:02:28
https://doi.org/10.1007/978-3-7091-4013-0onstraints are investigated. A preceding phase I (to obtain a good starting point) is discussed in conjunction with strategies to recognise the final active set as soon as possible. Finally, the convergence of the resulting 2-phase algorithm is proved.nauseate 发表于 2025-3-28 00:01:09
http://reply.papertrans.cn/16/1533/153214/153214_37.pngglomeruli 发表于 2025-3-28 03:43:08
http://reply.papertrans.cn/16/1533/153214/153214_38.pngFester 发表于 2025-3-28 07:34:50
http://reply.papertrans.cn/16/1533/153214/153214_39.pngASSAY 发表于 2025-3-28 10:53:17
https://doi.org/10.1007/978-3-642-47738-6r constraints, the issues to be discussed include incompatibility or ill-conditioning of the constraints, determination of the active set, Lagrange multiplier estimates, and approximation of the Lagrangian function.