Solving the Forward Kinematics of the 3RPR Planar Parallel Manipulator using a Hybrid Meta-Heuristic Paradigm

Date

2009-12-18

Author

Chandra, Rohitash
Zhang, Mengjie
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

152
views

0
downloads

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 algorithm shows better performance than the standard genetic algorithm.

Subject Keywords

Genetic algorithm, Tabu-search, Optimization

URI

https://hdl.handle.net/11511/66199

Collections

Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

A Meta-Heuristic Paradigm for solving the Forward Kinematics of 6-6 General Parallel Manipulator Chandra, Rohitash; Frean, Marcus; Rolland, Luc (2009-12-18) 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, t...
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...
Efficient and Accurate Electromagnetic Optimizations Based on Approximate Forms of the Multilevel Fast Multipole Algorithm Onol, Can; Karaosmanoglu, Bariscan; Ergül, Özgür Salih (2016-01-01) We present electromagnetic optimizations by heuristic algorithms supported by approximate forms of the multilevel fast multipole algorithm (MLFMA). Optimizations of complex structures, such as antennas, are performed by considering each trial as an electromagnetic problem that can be analyzed via MLFMA and its approximate forms. A dynamic accuracy control is utilized in order to increase the efficiency of optimizations. Specifically, in the proposed scheme, the accuracy is used as a parameter of the optimiz...
A hybrid evolutionary performance improvement procedure for optimisation of continuous variable discharge concentrators Sakuhuni, Givemore; Klein, Bern; Altun, Naci Emre (2015-05-05) An iterative hybrid performance improvement approach integrating artificial neural network modelling and Pareto genetic algorithm optimisation was developed and tested. The optimisation procedure, code named NNREGA, was tested for tuning pilot scale Continuous Variable Discharge Concentrator (CVD) in order to simultaneously maximise recovery and upgrade ratio of gold bearing sulphides from a polymetallic massive sulphide ore. For the tests the CVD was retrofitted during normal operation on the flotation tai...

Citation Formats

R. Chandra, M. Zhang, and L. Rolland, “Solving the Forward Kinematics of the 3RPR Planar Parallel Manipulator using a Hybrid Meta-Heuristic Paradigm,” 2009, p. 177, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/66199.