在企业云上使用子系统解决多目标问题
Multi-Objective Problem Solving With Offspring on Enterprise Clouds
摘要：
在本文中，我们提出了一个分布式实现的基于网络的多目标进化算法，称为EMO，通过使用后代。基于网络的进化算法已被证明是有效的多目标问题的解决。它们的特点是个体之间的连接网络，推动了算法的进化。不幸的是，它们需要大量的人口才能有效，分布式实现可以利用计算时间。大多数现有的框架仅限于提供基本或特定于给定算法的解决方案。我们的Offspring框架是一个基于插件的软件环境，允许在分布式计算环境（如企业云）上快速部署和执行进化算法。通过描述EMO的分布式实现，介绍了EMO的特点和优点。
英文摘要：
In this paper, we present a distributed implementation of a network based multi-objective evolutionary algorithm, called EMO, by using Offspring. Network based evolutionary algorithms have proven to be effective for multi-objective problem solving. They feature a network of connections between individuals that drives the evolution of the algorithm. Unfortunately, they require large populations to be effective and a distributed implementation can leverage the computation time. Most of the existing frameworks are limited to providing solutions that are basic or specific to a given algorithm. Our Offspring framework is a plug-in based software environment that allows rapid deployment and execution of evolutionary algorithms on distributed computing environments such as Enterprise Clouds. Its features and benefits are presented by describing the distributed implementation of EMO.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
