Generalized truncated methods for an efficient solution of retrial systems.
Genetic algorithm based method of elimination of residual oscillation in mechatronic systems
The paper presents control signals generation methods, preventing the excitation of residual vibration in slightly damped oscillational systems. It is focused on the feedforward methods, as most of the vibrations in examined processes are induced by the control, while the influence of disturbances is mostly negligible. Application of these methods involves ensuring of the insensitivity to natural frequency change, which can be reached in classical approach only by considerable increase of transient...
Genetic algorithm for combinatorial path planning: the subtour problem.
Genetic algorithm for network cost minimization using threshold based discounting.
Genetic Algorithms and Smoothing Filters in Solving the Geophysical Inversion Problem
Genetic and combinatorial algorithms for optimal sizing and placement of active power filters
The paper deals with cost effective compensator placement and sizing. It becomes one of the most important problems in contemporary electrical networks, in which voltage and current waveform distortions increase year-by-year reaching or even exceeding limit values. The suppression of distortions could be carried out by means of three types of compensators, i.e., passive filters, active power filters and hybrid filters. So far, passive filters have been more popular mainly because of economic reasons,...
Genetic and Tabu search algorithms for peptide assembly problem
Determining amino acid sequences of protein molecules is one of the most important issues in molecular biology. These sequences determine protein structure and functionality. Unfortunately, direct biochemical methods for reading amino acid sequences can be used for reading short sequences only. This is the reason, which makes peptide assembly algorithms an important complement of these methods. In this paper, a genetic algorithm solving the problem of short amino acid sequence assembly is presented....
Greedy algorithms for optimal computing of matrix chain products involving square dense and triangular matrices
This paper addresses a combinatorial optimization problem (COP), namely a variant of the (standard) matrix chain product (MCP) problem where the matrices are square and either dense (i.e. full) or lower/upper triangular. Given a matrix chain of length n, we first present a dynamic programming algorithm (DPA) adapted from the well known standard algorithm and having the same O(n3) complexity. We then design and analyse two optimal O(n) greedy algorithms leading in general to different optimal solutions...
Greedy algorithms for optimal computing of matrix chain products involving square dense and triangular matrices
This paper addresses a combinatorial optimization problem (COP), namely a variant of the (standard) matrix chain product (MCP) problem where the matrices are square and either dense (i.e. full) or lower/upper triangular. Given a matrix chain of length n, we first present a dynamic programming algorithm (DPA) adapted from the well known standard algorithm and having the same O(n3) complexity. We then design and analyse two optimal O(n) greedy algorithms leading in general to different optimal solutions...
GTES : une méthode de simulation par jeux et apprentissage pour l'analyse des systèmes d'acteurs
Cet article décrit une approche de la modélisation d'un système d'acteurs, particulièrement adaptée à la modélisation des entreprises, fondée sur la théorie des jeux [11] et sur l'optimisation par apprentissage du comportement de ces acteurs. Cette méthode repose sur la combinaison de trois techniques : la simulation par échantillonnage (Monte-Carlo), la théorie des jeux pour ce qui concerne la recherche d'équilibre entre les stratégies, et les méthodes heuristiques d'optimisation locale,...