Transactions of FAMENA, Vol. 50 No. 3, 2026.
Original scientific paper
https://doi.org/10.21278/TOF.503082825
A Dynamic Multi-Objective Approach Using Interval Analysis and Genetic Algorithms
Safa El Hraiech
; Mechanical Engineering Laboratory (LGM), National Engineering School of Monastir, University of Monastir, Monastir, Tunisia
*
Youssef Chouaibi
; Mechanical Engineering Laboratory (LGM), National Engineering School of Monastir, University of Monastir, Monastir, Tunisia; Higher Institute for Technological Studies of Sidi Bouzid, Sidi Bouzid, Tunisia
Zouhaier Affi
; Mechanical Engineering Laboratory (LGM), National Engineering School of Monastir, University of Monastir, Monastir, Tunisia
* Corresponding author.
Abstract
This paper considers a multi-objective optimisation problem focusing on translational parallel manipulators. The proposed approach combines interval analysis with genetic algorithms to optimise the dynamic parameters of parallel manipulators. The objectives are to enhance the robot accuracy, while maximising the tolerance intervals of the parameters. This paper's contribution is to introduce an interval method to estimate the error bounds of a dynamic parallel manipulator within the desired workspace. A genetic algorithm is then applied to improve manipulator accuracy and reduce design costs. The resulting Pareto fronts illustrate the trade-off between each pair of objective functions.
Keywords
parallel manipulator; interval analysis; genetic algorithm; optimisation; uncertainty
Hrčak ID:
348159
URI
Publication date:
16.6.2026.
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