Building with ParadisEO reusable parallel and distributed evolutionary algorithms

被引:13
作者
Cahon, S [1 ]
Melab, N [1 ]
Talbi, EG [1 ]
机构
[1] Univ Sci & Tech Lille Flandres Artois, CNRS, UMR 8022, Lab Informat Fondamentale Lille, F-59655 Villeneuve Dascq, France
关键词
evolutionary algorithms; design and code reuse; parallel and distributed models; frameworks; performance and robustness;
D O I
10.1016/j.parco.2003.12.010
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Numerous parallel and distributed evolutionary algorithms (PDEAs) and their implementations have been proposed and are available on the Web. A robust approach to make easier their code and design reuse is the framework approach. In this paper, we present some existing frameworks for PDEAs and their development requirements, and propose a new C++ open source framework, named Parallel and distributed Evolving Objects (ParadisEO). ParadisEO is basically devoted to the reusable and flexible design of parallel and distributed metaheuristics, but we focus here only on PDEAs. Compared to other related frameworks, ParadisEO allows more reuse flexibility, and provides more implemented parallel and distributed models. Furthermore, these models can be exploited by the user in a transparent way, and deployed as well on shared memory multi-processors as on distributed memory machines. The architecture has been experimented on two real-world applications: the radio network design and the spectroscopic data mining. The experimental results demonstrate the efficiency and robustness of the different models. (C) 2004 Elsevier B.V. All rights reserved.
引用
收藏
页码:677 / 697
页数:21
相关论文
共 21 条
[21]   A taxonomy of hybrid metaheuristics [J].
Talbi, EG .
JOURNAL OF HEURISTICS, 2002, 8 (05) :541-564