Hybrid deterministic/stochastic algorithm for large sets of rate equations

A Three-terms Conjugate Gradient Algorithm for Solving Large-Scale Systems of Nonlinear Equations

Nonlinear conjugate gradient method is well known in solving large-scale unconstrained optimization problems due to it’s low storage requirement and simple to implement. Research activities on it’s application to handle higher dimensional systems of nonlinear equations are just beginning. This paper presents a Threeterm Conjugate Gradient algorithm for solving Large-Scale systems of nonlinear e...

A HYBRID MODIFIED GENETIC-NELDER MEAD SIMPLEX ALGORITHM FOR LARGE-SCALE TRUSS OPTIMIZATION

In this paper a hybrid algorithm based on exploration power of the Genetic algorithms and exploitation capability of Nelder Mead simplex is presented for global optimization of multi-variable functions. Some modifications are imposed on genetic algorithm to improve its capability and efficiency while being hybridized with Simplex method. Benchmark test examples of structural optimization with a...

Recursive constructions for large sets of resolvable hybrid triple systems

A numerical algorithm for solving a class of matrix equations

In this paper, we present a numerical algorithm for solving matrix equations $(A otimes B)X = F$  by extending the well-known Gaussian elimination for $Ax = b$. The proposed algorithm has a high computational efficiency. Two numerical examples are provided to show the effectiveness of the proposed algorithm.

Roman Dementiev Algorithm Engineering for Large Data Sets

In recent years, the development of theoretically I/O-efficient algorithms and data structures has received considerable attention. However, much less has been done to evaluate their performance, in particular with parallel disks or when running on large inputs with sizes that really require external memory. This thesis presents the software library Stxxl that enables practice-oriented experime...