Optimization of the Solder Joints of an Electronic Card Using Heuristic Algorithm

2017 ◽  
Vol 30 ◽  
pp. 39-48
Author(s):  
H. Hachimi ◽  
S. Assif ◽  
Y. Aoues ◽  
Abdelkhalak El Hami ◽  
Rachid Ellaia ◽  
...  
Keyword(s):  
Finite Element ◽  
Particle Swarm Optimization ◽  
Mechanical Behavior ◽  
Evolutionary Algorithm ◽  
Heuristic Algorithm ◽  
Hybrid Method ◽  
Electronic Systems ◽  
Swarm Optimization ◽  
Differential Evolutionary Algorithm ◽  
Performance Results

In this paper, a new hybrid method of optimization by the heuristics algorithms to evaluate the reliability of the electronic card by simulating its thermo-mechanical behavior is presented. A model of simulation by finite element is developed to consider the maximal deformations due to temperature; a mechanico- computing coupling is used to find the optimal structure. Embedded electronic systems are playing a very important role in several areas, such as in automotive, aerospace, telecommunications and medical sectors. To properly perform their functions, electronic systems must be reliable [18].This powerful and robust algorithm which is based on hybridization of Differential Evolutionary algorithm with Particle Swarm Optimization (PSO) gives performance results [7].

Optimization for an Electronic Card with a New Hybrid Method

2013 ◽  
Vol 682 ◽  
pp. 143-151 ◽  
Author(s):  
S. Assif ◽  
H. Hachimi ◽  
M. Agouzoul ◽  
Rachid Ellaia ◽  
A. El Hami ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Finite Element ◽  
Particle Swarm Optimization ◽  
Mechanical Behavior ◽  
Hybrid Method ◽  
Optimal Structure ◽  
Electronic Systems ◽  
Swarm Optimization ◽  
Robust Algorithm ◽  
Performance Results

Embedded electronic systems are playing a very important role in several areas, such as in automotive, aerospace, telecommunications and medical sectors. To properly perform their functions, electronic systems must be reliable [2. So in this paper, we present a new hybrid method of optimization by the heuristics algorithms to evaluate the reliability of the electronic card by simulating its thermo-mechanical behavior. A model of simulation by finite element is developed to consider the maximal deformations due to the temperature; a mechanico-computing coupling is used to find the optimal structure. This powerful and robust algorithm which is based on hybridation of Genetic algorithm with Particle swarm optimization PSO gives performance results.

scholarly journals A Hybrid Newton–Raphson and Particle Swarm Optimization Method for Target Motion Analysis by Batch Processing

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2033
Author(s):  
Raegeun Oh ◽  
Yifang Shi ◽  
Jee Woong Choi
Keyword(s):  
Particle Swarm Optimization ◽  
Motion Analysis ◽  
Hybrid Method ◽  
Heuristic Algorithms ◽  
Particle Swarm ◽  
Optimization Method ◽  
Batch Processing ◽  
Swarm Optimization ◽  
Newton Raphson ◽  
Target Motion Analysis

Bearing-only target motion analysis (BO-TMA) by batch processing remains a challenge due to the lack of information on underwater target maneuvering and the nonlinearity of sensor measurements. Traditional batch estimation for BO-TMA is mainly performed based on deterministic algorithms, and studies performed with heuristic algorithms have recently been reported. However, since the two algorithms have their own advantages and disadvantages, interest in a hybrid method that complements the disadvantages and combines the advantages of the two algorithms is increasing. In this study, we proposed Newton–Raphson particle swarm optimization (NRPSO): a hybrid method that combines the Newton–Raphson method and the particle swarm optimization method, which are representative methods that utilize deterministic and heuristic algorithms, respectively. The BO-TMA performance obtained using the proposed NRPSO was tested by varying the measurement noise and number of measurements for three targets with different maneuvers. The results showed that the advantages of both methods were well combined, which improved the performance.

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