Approach of a Solution Construction Method for Mesh Router Placement Optimization Problem

Author(s):  
Aoto Hirata ◽  
Tetsuya Oda ◽  
Nobuki Saito ◽  
Kazuho Kanahara ◽  
Masaharu Hirota ◽  
...  
Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 857
Author(s):  
Jahedul Islam ◽  
Md Shokor A. Rahaman ◽  
Pandian M. Vasant ◽  
Berihun Mamo Negash ◽  
Ahshanul Hoqe ◽  
...  

Well placement optimization is considered a non-convex and highly multimodal optimization problem. In this article, a modified crow search algorithm is proposed to tackle the well placement optimization problem. This article proposes modifications based on local search and niching techniques in the crow search algorithm (CSA). At first, the suggested approach is verified by experimenting with the benchmark functions. For test functions, the results of the proposed approach demonstrated a higher convergence rate and a better solution. Again, the performance of the proposed technique is evaluated with well placement optimization problem and compared with particle swarm optimization (PSO), the Gravitational Search Algorithm (GSA), and the Crow search algorithm (CSA). The outcomes of the study revealed that the niching crow search algorithm is the most efficient and effective compared to the other techniques.


2020 ◽  
Vol 141 ◽  
pp. 102767 ◽  
Author(s):  
Jahedul Islam ◽  
Pandian M. Vasant ◽  
Berihun Mamo Negash ◽  
Moacyr Bartholomeu Laruccia ◽  
Myo Myint ◽  
...  

Author(s):  
Claire Dumas ◽  
Stéphane Caro ◽  
Sébastien Garnier ◽  
Benoît Furet

Roboticists are faced with new challenges in robotic-based manufacturing. Up to now manufacturing operations that require both high stiffness and accuracy have been mainly realized by using computer numerical control machine tools. This paper aims to show that manufacturing finishing tasks can be performed with robotic cells knowing the process cutting phenomena and the robot stiffness throughout its Cartesian workspace. It makes sense that the finishing task of large parts would be cheaper with robots. However, machining robots have not been adapted for such operations yet. As a consequence, this paper introduces a methodology that aims to determine the best placement of the workpiece to be machined knowing the cutting forces exerted on the tool and the elastostatic model of the robot. In this vein, a machining quality criterion is proposed and an optimization problem is formulated. The KUKA KR270-2 robot is used as an illustrative example throughout the paper.


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