Resource allocation and optimization of simulation models based on improved genetic algorithm in high-throughput simulation

Wei Zhao, Yanlong Zhai*, Han Zhang, Duzheng Qing

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

For the resource allocation and optimization problem of simulation model in high-throughput simulation, an extended genetic algorithm was proposed to improve the throughput of the simulation application. New coding approach and fitness function were designed to satisfy the model dependency. Corresponding algorithm for generating the initial population was also investigated. The experimental results showed that the extended GA can optimize the resource allocation and achieve better performance and reduce the execution time of simulation applications.

Original languageEnglish
Title of host publicationTheory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems - 16th Asia Simulation Conference and SCS Autumn Simulation Multi-Conference, AsiaSim/SCS AutumnSim 2016, Proceedings
EditorsLin Zhang, Xiao Song, Yunjie Wu
PublisherSpringer Verlag
Pages632-641
Number of pages10
ISBN (Print)9789811026683
DOIs
Publication statusPublished - 2016
Event16th Asia Simulation Conference and SCS Autumn Simulation Multi-Conference, AsiaSim/SCS AutumnSim 2016 - Beijing, China
Duration: 8 Oct 201611 Oct 2016

Publication series

NameCommunications in Computer and Information Science
Volume645
ISSN (Print)1865-0929

Conference

Conference16th Asia Simulation Conference and SCS Autumn Simulation Multi-Conference, AsiaSim/SCS AutumnSim 2016
Country/TerritoryChina
CityBeijing
Period8/10/1611/10/16

Keywords

  • Genetic algorithm
  • High-throughput simulation
  • Resource allocation

Fingerprint

Dive into the research topics of 'Resource allocation and optimization of simulation models based on improved genetic algorithm in high-throughput simulation'. Together they form a unique fingerprint.

Cite this