A Structure Optimization for Hooklift Arm Device Based on the Genetic Algorithm

2012 ◽  
Vol 455-456 ◽  
pp. 1504-1508
Author(s):  
Huan Ming Chen ◽  
Da Wei Liu
Keyword(s):  
Genetic Algorithm ◽  
Optimal Design ◽  
Parameter Optimization ◽  
Structure Optimization ◽  
Optimization Method ◽  
Optimized Design ◽  
Design Decision ◽  
Original Design ◽  
Multi Objective ◽  
Engineering Constraint

Based on the theory of FEM, the hooklift arm is modeled with the FEM software, and the structure of the device is optimized with genetic algorithm in a multi-objective/multi-parameter optimization environment, which results in an optimal design decision of the hooklift arm device under the engineering constraint. Comparison between optimized design decision and original design decision shows that the optimization is correct and the proposed multi-objective/multi-parameter optimization method is effective in improving the hooklift arm device.

scholarly journals A Two-Stage Mono- and Multi-Objective Method for the Optimization of General UPS Parallel Manipulators

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 543
Author(s):  
Alejandra Ríos ◽  
Eusebio E. Hernández ◽  
S. Ivvan Valdez
Keyword(s):  
Genetic Algorithm ◽  
Performance Metrics ◽  
Tracking Error ◽  
Parallel Manipulators ◽  
Optimization Method ◽  
Statistical Hypothesis ◽  
Two Stage ◽  
Multi Objective ◽  
Second Stage ◽  
Conflicting Objectives

This paper introduces a two-stage method based on bio-inspired algorithms for the design optimization of a class of general Stewart platforms. The first stage performs a mono-objective optimization in order to reach, with sufficient dexterity, a regular target workspace while minimizing the elements’ lengths. For this optimization problem, we compare three bio-inspired algorithms: the Genetic Algorithm (GA), the Particle Swarm Optimization (PSO), and the Boltzman Univariate Marginal Distribution Algorithm (BUMDA). The second stage looks for the most suitable gains of a Proportional Integral Derivative (PID) control via the minimization of two conflicting objectives: one based on energy consumption and the tracking error of a target trajectory. To this effect, we compare two multi-objective algorithms: the Multiobjective Evolutionary Algorithm based on Decomposition (MOEA/D) and Non-dominated Sorting Genetic Algorithm-III (NSGA-III). The main contributions lie in the optimization model, the proposal of a two-stage optimization method, and the findings of the performance of different bio-inspired algorithms for each stage. Furthermore, we show optimized designs delivered by the proposed method and provide directions for the best-performing algorithms through performance metrics and statistical hypothesis tests.

GA-Based Optimal Design of Derricking Balance Mechanism of Bucket Wheel Stacker Reclaimer

2012 ◽  
Vol 562-564 ◽  
pp. 672-675
Author(s):  
Man Ping Zhao
Keyword(s):  
Genetic Algorithm ◽  
Optimal Design ◽  
Cost Efficiency ◽  
Loading Condition ◽  
Matlab Toolbox ◽  
Multi Objective ◽  
Optimum Model ◽  
Balance Mechanism

The balancing system of a four-bar mechanism is frequently applied for bucket staking-reclaiming machines. For this purpose, a Multi-objective optimum model is developed in this study. Moreover, Genetic Algorithm is used for optimal design of the derricking mechanism and further programmed using MATLAB toolbox. To this end, this approach improves the mechanism performance, loading condition and cost-efficiency.

Study of the Non-Dominated Sorting Genetic Algorithm for the Optimal Structural Parameter of the Tooth-Arrangement Multi-Fingered Dextrous Hand

2013 ◽  
Vol 756-759 ◽  
pp. 4082-4089
Author(s):  
Zhan Li Li ◽  
Xiang Ting He
Keyword(s):  
Genetic Algorithm ◽  
Parameter Optimization ◽  
Experimental Results ◽  
Structural Parameter ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Pareto Solution ◽  
Multi Objective ◽  
Dextrous Hand

Firstly, the structural parameter optimization of the tooth-arrangement multi-fingered dextrous hand is studied. Secondly, as to the shortcomings that the Pareto solution of multi-objective optimization was distributed unevenly in NSGA-II, a non-dominated sorting genetic algorithm based on immune principle is proposed. Lastly, the structural parameter of the medical tooth-arrangement multi-fingered dextrous hand is optimized using the proposed algorithm. The experimental results show that this algorithm can optimize structural parameter of tooth-arrangement multi-fingered dextrous hand very well.

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