scholarly journals Optimization on kinematic characteristics and lightweight of a camellia fruit picking machine based on the Kriging surrogate model

2021 ◽  
Vol 22 ◽  
pp. 16
Author(s):  
Di Kang ◽  
Ze Jun Chen ◽  
You Hua Fan ◽  
Cheng Li ◽  
Chengji Mi ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Surrogate Model ◽  
Design Variable ◽  
Optimal Solution ◽  
Kriging Surrogate Model ◽  
Maximum Acceleration ◽  
Rotating Speed ◽  
Working Principle ◽  
The Relationship ◽  
Executive Body

In order to achieve fully automated picking of camellia fruit and overcome the technical difficulties of current picking machinery such as inefficient service and manual auxiliary picking, a novel multi-links-based picking machine was proposed in this paper. The working principle and process of this device was analyzed. The mechanism kinematics equation was given, and the velocity executive body was obtained, as well as the acceleration. The acceleration at pivotal positions was tested in the camellia fruit forest, and the simulated results agreed well with the experimental ones. Then, the maximum acceleration of executive body and weight was considered as the optimization objective, and the rotating speed of crank, the radius and thickness of crank and the length and radius of link rod were regarded as the design variable. Based on the Kriging surrogate model, the relationship between variables and optimization objectives was built, and their interrelations were analyzed. Finally, the optimal solution was acquired by the non-dominated sorting genetic algorithm II, which resulted in the reduction of the maximum acceleration of executive body by 31.30%, as well as decrease of weight by 27.51%.

A Kriging surrogate model assisted Tabu search method for electromagnetic inverse problems

2020 ◽  
Vol 64 (1-4) ◽  
pp. 351-358
Author(s):  
Siguang An ◽  
Qiang Deng ◽  
Tianwei Wu ◽  
Shiyou Yang ◽  
Nanying Shentu
Keyword(s):  
Inverse Problems ◽  
Tabu Search ◽  
Surrogate Model ◽  
Optimal Solution ◽  
Search Method ◽  
Computational Time ◽  
Mathematical Function ◽  
Kriging Surrogate Model ◽  
Variable Space ◽  
Tabu Search Method

To balance the efficiency and accuracy of a global optimization algorithm in solving electromagnetic inverse problems, a Tabu search method assisted by using a Kriging surrogate model is proposed. To reduce the computational time and speed up the algorithm, the Kriging surrogate model is used to predict the objective space. To ensure the accuracy of the final optimal solution, a united trigger is developed to realize dynamically switching between the prediction and the direct objective computation. To utilize the variable space efficiently and provide proper sampling points to update the Kriging surrogate model, an evaluation list is used to evaluate the variable space. A typical mathematical function and electromagnetic inverse problems in low and high frequency are solved to testify the correctness and effectiveness of the proposed method.

Kriging Surrogate Model based Optimisation of Welded Bogie Frame for Fatigue Improvement

2019 ◽  
Vol 11 (4) ◽  
Author(s):  
Yuehua Gao ◽  
Qipeng Liu ◽  
Dan Zhao
Keyword(s):  
Genetic Algorithm ◽  
Approximate Method ◽  
Response Surface ◽  
Surrogate Model ◽  
Fatigue Improvement ◽  
Surface Sampling ◽  
Kriging Surrogate Model ◽  
Bogie Frame ◽  
Multiple Unit ◽  
Optimisation Model

The welded side frame of intercity Electric Multiple Unit (EMU) bogie frame is taken as the research objective to optimize the layout of its internal stiffeners and to improve its fatigue performance. The fatigue accumulation damage value is computed in side frame for some key welds using Master S-N curve approach and the maximal value of fatigue accumulation damage is considered as a significant constraint to construct a lightweight optimisation model. To solve the optimisation model effectively, a sequential approximate method on the basis of Kriging surrogate model is presented by combining the minimum response surface sampling with multi-island genetic algorithm. The weight of the side frame is reduced by 16% after optimisation, which realized the fatigue improvement.

Optimization Design of the Crane Girder Based on Adaptive Genetic Algorithm

2012 ◽  
Vol 591-593 ◽  
pp. 123-126
Author(s):  
Peng Fei Wang ◽  
Xiu Hui Diao
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Design Variable ◽  
Optimization Design ◽  
Optimal Solution ◽  
Population Diversity ◽  
Main Beam ◽  
Gantry Crane ◽  
Adaptive Genetic Algorithm ◽  
Accelerate Convergence

With taking weight of single main beam of gantry crane as objective function, and taking main beam upper & lower cored, diagonal & horizontal bracing, and width & weight as design variable, this essay adopted population diversity adaptive genetic algorithm to optimize its structure and improved program design through MATLAB. This algorithm could accelerate convergence speed, which make much it easier to realize comprehensive optimal solution, since it effectively avoided weakness of basic genetic algorithm, such as partial optimal solution, prematurity and being lack of continuity, etc.

Optimization of Balloon-Stent System Based on Nonlinear Material Using Kriging Surrogate Model

2012 ◽  
Vol 502 ◽  
pp. 463-468
Author(s):  
Hong Xia Li ◽  
Xi Cheng Wang
Keyword(s):  
Surrogate Model ◽  
Design Space ◽  
Optimization Method ◽  
Nonlinear Material ◽  
Kriging Surrogate Model ◽  
Adaptive Optimization ◽  
Model Combining ◽  
Stent System ◽  
Global Optimal ◽  
The Relationship

Computer-aided technology was used for balloon-stent system design. Nonlinear material was used to simulate the dilation of balloon-stent system. Based on finite element results, an adaptive optimization method based on the kriging surrogate model combining with LHS approach and EI function was employed for the optimization of balloon length to reduce stent dogboning effect during its dilation. The kriging surrogate model can approximate the relationship between dogboning rate and balloon length, replacing the expensive reanalysis of the stent dilation. Sample points from LHS can represent the information of all parts on the design space. EI function is used to balance local and global search, and tends to find the global optimal design. Numerical results demonstrate that this adaptive optimization methed based on kriging surrogate model can be used for the optimization of balloon length of balloon-stent system.

scholarly journals Global Simultaneous Optimization of Oil, Hysteretic and Inertial Dampers Using Real-Valued Genetic Algorithm and Local Search

2021 ◽  
Vol 7 ◽  
Author(s):  
Ryohei Uemura ◽  
Hiroki Akehashi ◽  
Kohei Fujita ◽  
Izuru Takewaki
Keyword(s):  
Genetic Algorithm ◽  
Local Search ◽  
Optimal Solution ◽  
Optimization Method ◽  
Simultaneous Optimization ◽  
Global Optimality ◽  
Building Structures ◽  
Global Optimal Solution ◽  
Maximum Acceleration ◽  
Global Optimal

A method for global simultaneous optimization of oil, hysteretic and inertial dampers is proposed for building structures using a real-valued genetic algorithm and local search. Oil dampers has the property that they can reduce both displacement and acceleration without significant change of natural frequencies and hysteretic dampers possess the characteristic that they can absorb energy efficiently and reduce displacement effectively in compensation for the increase of acceleration. On the other hand, inertial dampers can change (prolong) the natural periods with negative stiffness and reduce the effective input and the maximum acceleration in compensation for the increase of deformation. By using the proposed simultaneous optimization method, structural designers can select the best choice of these three dampers from the viewpoints of cost and performance indices (displacement, acceleration). For attaining the global optimal solution which cannot be attained by the conventional sensitivity-based approach, a method including a real-valued genetic algorithm and local search is devised. In the first stage, a real-valued genetic algorithm is used for searching an approximate global optimal solution. Then a local search procedure is activated for enhancing the optimal character of the solutions by reducing the total quantity of three types of dampers. It is demonstrated that a better design from the viewpoint of global optimality can be obtained by the proposed method and the preference of damper selection strongly depends on the design target (displacement, acceleration). Finally, a multi-objective optimization for the minimum deformation and acceleration is investigated.

Optimization of Vaneless Volute and Mixed Flow Impeller for Pulsating Flow

2020 ◽  
Author(s):  
Zheng Liu ◽  
Colin Copeland ◽  
Stefan Tuechler
Keyword(s):  
Genetic Algorithm ◽  
Optimization Algorithm ◽  
Surrogate Model ◽  
Influential Factor ◽  
Design Parameters ◽  
Angle Distribution ◽  
Kriging Surrogate Model ◽  
Mixed Flow ◽  
Turbine Performance ◽  
Percentage Points

Abstract Vaneless turbocharger turbines are commonly used for automotive engines due to their low cost and better off-design performance. It consists of a vaneless volute and a radial or mixed flow rotor, where both components are important to the overall device performance. With the pulsating nature of the exhaust flows, most energy is contained at the peak of the pulse. Therefore, during one engine cycle, optimizing the turbine performance for the peak pulse region is more straightforward to improve the cycle-averaged shaft power generation. This study sought to optimize both the volute and rotor simultaneously for the peak point of the pressure pulse (2.4 bar). Thirteen design parameters in total are considered during the optimization process. Six volute design parameters were used to control the aspect ratio, intake area, exit area, and the circumferential distribution of the cross-sectional area. Seven rotor parameters were utilized to modify the cone angle, blade axial location, and the camber-line angle distribution. The optimization was conducted by a novel optimization algorithm based on Kriging surrogate model, and compared with the conventional genetic algorithm. Commercial turbulent viscous CFD solver ANSYS-CFX was used to predict the turbine performance. Full-stage turbine, including ten blade passages, is explicitly modeled for better accuracy. In order to ensure the matching between turbocharger and engine maintained the same as the original turbine, special attention was paid to constraint the swallowing capacity characteristic of the optimized turbine to be similar to the baseline turbine, with a maximum 2.5% difference at the design point. Compared with the baseline turbine, the turbine efficiency was improved by 3 percentage points with the using the genetic algorithm, and an improvement of 3.65 percentage points was achieved by using the Kriging surrogate model based optimization algorithm. Although the optimized turbine has a lower peak efficiency, the optimal velocity ratio of optimized design shifted from the baseline value of 0.71 to 0.61, implying a better performance will be achieved under high loading conditions. The improvement of the turbine performance is attributed to a better blade loading that is achieved in the 0.2–0.4 stream-wise location. The elementary effectiveness has been studied, and the camber-line distribution of the rotor is found to be the most influential factor on the turbine performance.

scholarly journals Inclusion of Hydraulic Controls in Rehabilitation Models of Drainage Networks to Control Floods

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 514
Author(s):  
Leonardo Bayas-Jiménez ◽  
F. Javier Martínez-Solano ◽  
Pedro L. Iglesias-Rey ◽  
Daniel Mora-Melia ◽  
Vicente S. Fuertes-Miquel
Keyword(s):  
Genetic Algorithm ◽  
Drainage System ◽  
Optimal Solution ◽  
Hydraulic Control ◽  
Drainage Systems ◽  
Storm Water Management Model ◽  
Drainage Networks ◽  
Extreme Rain ◽  
Rain Events ◽  
The Cost

A problem for drainage systems managers is the increase in extreme rain events that are increasing in various parts of the world. Their occurrence produces hydraulic overload in the drainage system and consequently floods. Adapting the existing infrastructure to be able to receive extreme rains without generating consequences for cities’ inhabitants has become a necessity. This research shows a new way to improve drainage systems with minimal investment costs, using for this purpose a novel methodology that considers the inclusion of hydraulic control elements in the network, the installation of storm tanks and the replacement of pipes. The presented methodology uses the Storm Water Management Model for the hydraulic analysis of the network and a modified Genetic Algorithm to optimize the network. In this algorithm, called the Pseudo-Genetic Algorithm, the coding of the chromosomes is integral and has been used in previous studies of hydraulic optimization. This work evaluates the cost of the required infrastructure and the damage caused by floods to find the optimal solution. The main conclusion of this study is that the inclusion of hydraulic controls can reduce the cost of network rehabilitation and decrease flood levels.

scholarly journals Business E-NeGotiAtion: A Method Using a Genetic Algorithm for Online Dispute Resolution in B2B Relationships

2021 ◽  
Vol 16 (5) ◽  
pp. 1186-1216
Author(s):  
Nikola Simkova ◽  
Zdenek Smutny
Keyword(s):  
Genetic Algorithm ◽  
Dispute Resolution ◽  
Single Case ◽  
Computer Mediated Communication ◽  
Optimal Solution ◽  
Mediated Communication ◽  
Online Dispute Resolution ◽  
B2b Relationships ◽  
Definition Of ◽  
E Mail

An opportunity to resolve disputes as an out-of-court settlement through computer-mediated communication is usually easier, faster, and cheaper than filing an action in court. Artificial intelligence and law (AI & Law) research has gained importance in this area. The article presents a design of the E-NeGotiAtion method for assisted negotiation in business to business (B2B) relationships, which uses a genetic algorithm for selecting the most appropriate solution(s). The aim of the article is to present how the method is designed and contribute to knowledge on online dispute resolution (ODR) with a focus on B2B relationships. The evaluation of the method consisted of an embedded single-case study, where participants from two countries simulated the realities of negotiation between companies. For comparison, traditional negotiation via e-mail was also conducted. The evaluation confirms that the proposed E-NeGotiAtion method quickly achieves solution(s), approaching the optimal solution on which both sides can decide, and also very importantly, confirms that the method facilitates negotiation with the partner and creates a trusted result. The evaluation demonstrates that the proposed method is economically efficient for parties of the dispute compared to negotiation via e-mail. For a more complicated task with five or more products, the E-NeGotiAtion method is significantly more suitable than negotiation via e-mail for achieving a resolution that favors one side or the other as little as possible. In conclusion, it can be said that the proposed method fulfills the definition of the dual-task of ODR—it resolves disputes and builds confidence.

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