Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
A Meta-Heuristic Paradigm for solving the Forward Kinematics of 6-6 General Parallel Manipulator
Date
2009-12-18
Author
Chandra, Rohitash
Frean, Marcus
Rolland, Luc
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
283
views
0
downloads
Cite This
The forward kinematics of the general Gough platform, namely the 6-6 parallel manipulator is solved using hybrid meta-heuristic techniques in which the simulated annealing algorithm replaces the mutation operator in a genetic algorithm. The results are compared with the standard simulated annealing and genetic algorithm. It shows that the standard simulated annealing algorithm outperforms standard genetic algorithm in terms of computation time and overall accuracy of the solution on this problem. However, the hybrid meta-heuristic paradigm shows the best performance in terms of accuracy and success rate.
Subject Keywords
Neural-network
,
Tabu-search
,
Optimization
,
Algorithms
,
Performance
URI
https://hdl.handle.net/11511/66922
Collections
Department of Computer Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
Solving the Forward Kinematics of the 3RPR Planar Parallel Manipulator using a Hybrid Meta-Heuristic Paradigm
Chandra, Rohitash; Zhang, Mengjie; Rolland, Luc (2009-12-18)
The forward kinematic of the 3-RPR parallel manipulator is solved using a hybrid meta-heuristic technique where the simulated annealing algorithm replaces the mutation operator in a genetic algorithm. The results from the hybrid meta-heuristic approach is compared with the standard simulated annealing and genetic algorithm. The results show that the simulated annealing algorithm outperforms genetic algorithm in terms of computation time and overall accuracy of the solution. The hybrid meta-heuristic search ...
A parallel ant colony optimization algorithm based on crossover operation
Kalınlı, Adem; Sarıkoç, Fatih (Springer, 2018-11-01)
In this work, we introduce a new parallel ant colony optimization algorithm based on an ant metaphor and the crossover operator from genetic algorithms.The performance of the proposed model is evaluated usingwell-known numerical test problems and then it is applied to train recurrent neural networks to identify linear and nonlinear dynamic plants. The simulation results are compared with results using other algorithms.
A neural network method for direction of arrival estimation with uniform circular dipole array in the presence of mutual coupling
Caylar, Selcuk; Leblebicioğlu, Mehmet Kemal; Dural, Guelbin (2007-06-16)
In recent years application of Neural Network (NN) algorithms in both target tracking problem and DoA estimation have become popular because of the increased computational efficiency This paper presents the implementation of modified neural network algorithm(MN-MUST) to the uniform circular dipole array in the presence of mutual coupling. In smart antenna systems, mutual coupling between elements can significantly degrade the processing algorithms. In this paper mutual coupling affects on MN-MUST has been i...
An interactive preference based multiobjective evolutionary algorithm for the clustering problem
Demirtaş, Kerem; Özdemirel, Nur Evin; Karasakal, Esra; Department of Industrial Engineering (2011)
We propose an interactive preference-based evolutionary algorithm for the clustering problem. The problem is highly combinatorial and referred to as NP-Hard in the literature. The goal of the problem is putting similar items in the same cluster and dissimilar items into different clusters according to a certain similarity measure, while maintaining some internal objectives such as compactness, connectivity or spatial separation. However, using one of these objectives is often not sufficient to detect differ...
A hybrid genetic algorithm for the discrete time-cost trade-off problem
Sönmez, Rifat (2012-10-01)
In this paper we present a hybrid strategy developed using genetic algorithms (GAs), simulated annealing (SA), and quantum simulated annealing techniques (QSA) for the discrete time-cost trade-off problem (DTCTP). In the hybrid algorithm (HA), SA is used to improve hill-climbing ability of GA. In addition to SA, the hybrid strategy includes QSA to achieve enhanced local search capability. The HA and a sole GA have been coded in Visual C++ on a personal computer. Ten benchmark test problems with a range of 1...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
R. Chandra, M. Frean, and L. Rolland, “A Meta-Heuristic Paradigm for solving the Forward Kinematics of 6-6 General Parallel Manipulator,” 2009, p. 171, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/66922.