In this paper a genetic algorithm based reconfiguration method is proposed to minimize the real power losses of distribution systems. The main innovation of this research work is that new types of crossover and mutation ...

An enhanced genetic algorithm (EGA) is applied to solve the long-term transmission expansion planning (LTTEP) problem. The following characteristics of the proposed EGA to solve the static and multistage LTTEP problem are ...

We present an algorithm which attempts to align pairs of subsequences from a database of genetic sequences. The algorithm simulates the classical dynamic programming alignment algorithm over a suffix array of the database. ...

In most transformations from dedicated to modular approaches, products are assumed to have a unique modular structure. However, it is well known that alternatives for constructing modular structures may exist in any level ...

This paper analyses the impact of choosing good initial populations for genetic algorithms regarding convergence speed and final solution quality. Test problems were taken from complex electricity distribution network ...

This paper presents a mixed integer nonlinear programming multiobjective model for short-term planning of distribution networks that considers in an integrated manner the following planning activities: allocation of capacitor ...

In this paper the genetic algorithm of Chu and Beasley (GACB) is applied to solve the static and multistage transmission expansion planning problem. The characteristics of the GACB, and some modifications that were done, ...

The paper presents an extended genetic algorithm for solving the optimal transmission network expansion planning problem. Two main improvements have been introduced in the genetic algorithm: (a) initial population obtained ...