Harmony search algorithm and related variants: A systematic review
Harmony search (HS) algorithm is a novel metaheuristic algorithm, inspired by the
phenomenon that musicians repeatedly adjust the pitch of each instrument to finally achieve …
phenomenon that musicians repeatedly adjust the pitch of each instrument to finally achieve …
On three-term conjugate gradient method for optimization problems with applications on COVID-19 model and robotic motion control
The three-term conjugate gradient (CG) algorithms are among the efficient variants of CG
algorithms for solving optimization models. This is due to their simplicity and low memory …
algorithms for solving optimization models. This is due to their simplicity and low memory …
[PDF][PDF] An efficient DY-type spectral conjugate gradient method for system of nonlinear monotone equations with application in signal recovery
Many problems in engineering and social sciences can be transformed into system of
nonlinear equations. As a result, a lot of methods have been proposed for solving the …
nonlinear equations. As a result, a lot of methods have been proposed for solving the …
A new generalized quasi-newton algorithm based on structured diagonal hessian approximation for solving nonlinear least-squares problems with application to 3dof …
Many problems in science and engineering can be formulated as nonlinear least-squares
(NLS) problems. Thus, the need for efficient algorithms to solve these problems can not be …
(NLS) problems. Thus, the need for efficient algorithms to solve these problems can not be …
Structured adaptive spectral-based algorithms for nonlinear least squares problems with robotic arm modelling applications
This research article develops two adaptive, efficient, structured non-linear least-squares
algorithms, NLS. The approach taken to formulate these algorithms is motivated by the …
algorithms, NLS. The approach taken to formulate these algorithms is motivated by the …
A New Variant of the Conjugate Descent Method for Solving Unconstrained Optimization Problems and Applications.
Unconstrained optimization problems have a long history in computational mathematics and
have been identified as being among the crucial problems in the fields of applied sciences …
have been identified as being among the crucial problems in the fields of applied sciences …
Alternative structured spectral gradient algorithms for solving nonlinear least-squares problems
The study of efficient iterative algorithms for addressing nonlinear least-squares (NLS)
problems is of great importance. The NLS problems, which belong to a special class of …
problems is of great importance. The NLS problems, which belong to a special class of …
A Modified Dai–Liao Conjugate Gradient Method Based on a Scalar Matrix Approximation of Hessian and Its Application
We introduce and investigate proper accelerations of the Dai–Liao (DL) conjugate gradient
(CG) family of iterations for solving large‐scale unconstrained optimization problems. The …
(CG) family of iterations for solving large‐scale unconstrained optimization problems. The …
A Modified Structured Spectral HS Method for Nonlinear Least Squares Problems and Applications in Robot Arm Control
This paper proposes a modification to the Hestenes-Stiefel (HS) method by devising a
spectral parameter using a modified secant relation to solve nonlinear least-squares …
spectral parameter using a modified secant relation to solve nonlinear least-squares …
On diagonally structured scheme for nonlinear least squares and data-fitting problems
Recently, structured nonlinear least-squares (NLS) based algorithms gained considerable
emphasis from researchers; this attention may result from increasingly applicable areas of …
emphasis from researchers; this attention may result from increasingly applicable areas of …