| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 381727 | Engineering Applications of Artificial Intelligence | 2007 | 7 Pages |
Abstract
This paper presents a discrete optimization system implementing a parallel hybrid metaheuristic. This is obtained by joining a genetic algorithm and a parallel version of a stochastic descent method called ‘Kangaroo’. Two real problems in the manufacturing field were solved using the proposed metaheuristic. This offered the opportunity to underline some aspects regarding the implementation of this hybrid system. The impact of the precedence constraints upon the implementation of the genetic operators (crossover and mutation) is also considered.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Viorel Minzu, Liviu Beldiman,