分布式基于web的仿真实验优化

Enver Yücesan , Yuh-Chuyn Luo , Chun-Hung Chen , Insup Lee
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引用次数: 38

摘要

在过去的十年里,网络发展迅猛,应用于教育、市场营销、金融服务和供应链管理。网络技术也对计算机仿真产生了重大影响。基于web的仿真中的大部分工作都是针对建模的,特别是构建仿真语言和创建可以在web上组装和执行的模型库。本文的重点是优化仿真实验的效率。我们引入了一个框架,将仿真优化技术的统计效率与并行执行算法的有效性相结合。特别提出了一种新颖的仿真采样过程,即最优计算预算分配(OCBA)算法,该算法在基于web的环境中实现,用于低成本的并行和分布式仿真实验。给出了一个原型实现和一些实验结果,以证明网络仿真环境的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed web-based simulation experiments for optimization

The web has grown tremendously over the past decade – with applications in education, marketing, financial services, and supply chain management. Web technology also has a significant impact on computer simulation. Most of the effort in web-based simulation is aimed at modeling, particularly at building simulation languages and at creating model libraries that can be assembled and executed over the web. This paper focuses on efficiency of simulation experimentation for optimization. We introduce a framework for combining the statistical efficiency of simulation optimization techniques with the effectiveness of parallel execution algorithms. In particular, a novel simulation sampling procedure, the Optimal Computing Budget Allocation (OCBA) algorithm, is implemented in a web-based environment for low-cost parallel and distributed simulation experimentation. A prototype implementation with some experimental results is presented to show the viability of web-enabled simulation environments.

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