Paper Info
Title
A Hybrid EDA/Nelder-Mead for Concurrent Robot Optimization.
Abstract
We introduce an optimization algorithm which combines an Estimation of Distribution Algorithm (EDA) and the Nelder-Mead method for global and local optimization, respectively. The proposal not only interleaves global and local search steps but takes advantage of the information collected by the global search to use it into the local search and backwards, providing of an efficient symbiosis. The algorithm is applied to the concurrent optimization of a rehabilitation robot design, that is to say, to the dimensional synthesis as well as the determination of control gains. Finally, we present an statistical analysis and evidence about the performance of this symbiotic algorithm.
Year
DOI
Venue
2018
10.1007/978-3-030-14347-3_20
HIS
Field
DocType
Citations 
Mathematical optimization,Estimation of distribution algorithm,Computer science,Rehabilitation robot,Nelder–Mead method,Optimization algorithm,Local search (optimization),Robot,Statistical analysis
Conference
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
S. Ivvan Valdez100.68
Eusebio E. Hernandez213.41
Sajjad Keshtkar300.34