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2. Sufficient descent conjugate gradient methods for large-scale optimization problems.
3. A QP-free algorithm without a penalty function or a filter for nonlinear general-constrained optimization.
4. Conjugate gradient methods based on secant conditions that generate descent search directions for unconstrained optimization
5. A practical PR+ conjugate gradient method only using gradient
6. A new class of nonlinear conjugate gradient coefficients with global convergence properties
7. A new penalty-free-type algorithm based on trust region techniques
8. An SQP-filter method for inequality constrained optimization and its global convergence
9. An active set limited memory BFGS algorithm for bound constrained optimization
10. Modified active set projected spectral gradient method for bound constrained optimization
11. Combining nonmonotone conic trust region and line search techniques for unconstrained optimization
12. A new feasible descent primal–dual interior point algorithm for nonlinear inequality constrained optimization
13. A self-adaptive trust region method with line search based on a simple subproblem model
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