Abstract
A novel root based optimization algorithm (ROA), which mimics the proliferation of plant roots, is proposed to evaluate the performances of a multi-axial road test rig over a prescribed workspace. Plant roots have developed complex behavior patterns to search for nutrients in the soil and even exhibit swarm intelligence. The growing roots can adapt their actions such as elongation, branching, and tropistic movement according to the environment. During the process of foraging for water and nutrients, the adaptive growth behavior of roots can be simulated to tackle the optimization problem. The efficiency of the proposed ROA has been validated by comparing it with well-known intelligent algorithms using classical and IEEE CEC 2019 benchmark functions. Computational results indicate that ROA outperforms other algorithms to search a global optimum on several benchmarks. Furthermore, the results are tested with nonparametric statistical methods, e.g., Wilcoxon rank-sum test. Besides, ROA is applied to the optimal dimensioning synthesis of the multi-axial road test rig (MRTR) based on the orthogonal 6-RSS parallel manipulator to promote the device's performance. The inverse kinematics of the multi-axial road test rig based on the asymmetrical orthogonal 6-RSS parallel mechanism is analyzed in detail. Applying the achieved dimensionless Jacobian, the performance criteria involving the global isotropy index, the force/velocity transmissibility index, the decoupling index are established. By simultaneously taking account the proposed criteria of performance, structural optimization is carried out resorting to ROA. Finally, a set of optimized dimensional parameters is obtained. The practical application further illustrates that ROA has the potential to deal with complex optimization problems.
Highlights
INTRODUCTIONroot optimization algorithm (ROA) is applied to the optimal design of road test rig based on asymmetrical orthogonal 6-RSS parallel manipulator with a specific task
Many nature-inspired intelligence algorithms have been developed to address complex and nonlinear problems, which cannot be solved effectively by traditional methods
The results demonstrate high exploration and exploitation characteristics of the proposed root optimization algorithm (ROA) algorithm
Summary
ROA is applied to the optimal design of road test rig based on asymmetrical orthogonal 6-RSS parallel manipulator with a specific task. The growth mechanisms of roots are studied thoroughly and modeled mathematically including emission of primary roots, branching and re-growth, which combines swarm intelligence and evolutionary strategies to trade-off in both exploration and exploitation abilities.
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