Simulated parallel annealing within a neighborhood for optimization of biomechanical systems

Optimization problems for biomechanical systems have become extremely complex. Simulated annealing (SA) algorithms have performed well in a variety of test problems and biomechanical applications; however, despite advances in computer speed, convergence to optimal solutions for systems of even moder...

Full description

Saved in:
Bibliographic Details
Published in:Journal of biomechanics 2005-09, Vol.38 (9), p.1938-1942
Main Authors: Higginson, J.S., Neptune, R.R., Anderson, F.C.
Format: Article
Language:English
Subjects:
Algorithms
Bicycling - physiology
Biomechanical Phenomena - methods
Biomechanics
Communication
Computer Simulation
Forward dynamic simulation
Humans
Joints - physiology
Leg - physiology
Models, Biological
Muscle Contraction - physiology
Musculoskeletal modeling
Neighborhoods
Optimization
Optimization techniques
Parallel computing
Performance evaluation
Simulated annealing
Simulation
Transplants & implants
Variables
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Optimization problems for biomechanical systems have become extremely complex. Simulated annealing (SA) algorithms have performed well in a variety of test problems and biomechanical applications; however, despite advances in computer speed, convergence to optimal solutions for systems of even moderate complexity has remained prohibitive. The objective of this study was to develop a portable parallel version of a SA algorithm for solving optimization problems in biomechanics. The algorithm for simulated parallel annealing within a neighborhood (SPAN) was designed to minimize interprocessor communication time and closely retain the heuristics of the serial SA algorithm. The computational speed of the SPAN algorithm scaled linearly with the number of processors on different computer platforms for a simple quadratic test problem and for a more complex forward dynamic simulation of human pedaling.
ISSN:0021-9290
1873-2380
DOI:10.1016/j.jbiomech.2004.08.010