Metal Inert Gas (MIG) Welding Process Optimization using Teaching-Learning Based Optimization (TLBO) Algorithm

Teaching-learning-based optimization (TLBO) algorithm is proposed in recent years that simulates the teaching-learning phenomenon of a classroom to effectively solve global optimization of multidimensional, linear, and nonlinear problems over continuous spaces. In this paper, an improved teaching-learning-based optimization algorithm is presented, which is called nonlinear inertia weighted teaching-learning-based optimization (NIWTLBO) algorithm. This algorithm introduces a nonlinear inertia weighted factor into the basic TLBO to control the memory rate of learners and uses a dynamic inertia weighted factor to replace the original random number in teacher phase and learner phase. The proposed algorithm is tested on a number of benchmark functions, and its performance comparisons are provided against the basic TLBO and some other well-known optimization algorithms. The experiment results show that the proposed algorithm has a faster convergence rate and better performance than the basic TLBO and some other algorithms as well.

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ONU placement in Fiber-Wireless (FiWi) access networks using teacher phase of Teaching Learning Based Optimization (TLBO) algorithm

2017 3rd International Conference on Computational Intelligence & Communication Technology (CICT) ◽

10.1109/ciact.2017.7977312 ◽

2017 ◽

Cited By ~ 2

Author(s):

Uma Rathore Bhatt ◽

Nitin Chouhan ◽

Raksha Upadhyay ◽

Chanchal Agrawal

Keyword(s):

Access Networks ◽

Tlbo Algorithm ◽

Teaching Learning Based Optimization ◽

Teaching Learning

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Synthesis of Thinned Concentric Circular Antenna Arrays Using Modified TLBO Algorithm

International Journal of Antennas and Propagation ◽

10.1155/2015/586345 ◽

2015 ◽

Vol 2015 ◽

pp. 1-9 ◽

Cited By ~ 4

Author(s):

Zailei Luo ◽

Xueming He ◽

Xuedong Chen ◽

Xin Luo ◽

Xiaoqing Li

Keyword(s):

Antenna Arrays ◽

Optimization Problems ◽

Extended Space ◽

Half Wavelength ◽

Tlbo Algorithm ◽

Teaching Learning Based Optimization ◽

Teaching Learning ◽

Antenna Array Synthesis ◽

Circular Antenna Arrays ◽

Circular Antenna Array

Teaching-learning-based optimization (TLBO) algorithm is a new kind of stochastic metaheuristic algorithm which has been proven effective and powerful in many engineering optimization problems. This paper describes the application of a modified version of TLBO algorithm, MTLBO, for synthesis of thinned concentric circular antenna arrays (CCAAs). The MTLBO is adjusted for CCAA design according to the geometry arrangement of antenna elements. CCAAs with uniform interelement spacing fixed at half wavelength have been considered for thinning using MTLBO algorithm. For practical purpose, this paper demonstrated SLL reduction of thinned CCAAs in the whole regular and extended space other than the phi = 0° plane alone. The uniformly and nonuniformly excited CCAAs have been discussed, respectively, during the simulation process. The proposed MTLBO is very easy to be implemented and requires fewer algorithm specified parameters, which is suitable for concentric circular antenna array synthesis. Numerical results clearly show the superiority of MTLBO algorithm in finding optimum solutions compared to particle swarm optimization algorithm and firefly algorithm.

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A Cost Model for the Metal Inert Gas (MIG) Welding Process

Volume 4: ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications and the 19th Reliability, Stress Analysis, and Failure Prevention Conference ◽

10.1115/detc2007-35795 ◽

2007 ◽

Cited By ~ 1

Author(s):

Pradeep Kumar Tipaji ◽

Venkat Allada ◽

Rajiv Mishra

Keyword(s):

Cost Estimation ◽

Material Selection ◽

Cost Model ◽

Welding Process ◽

Inert Gas ◽

Mig Welding ◽

Estimation Model ◽

Cost Component ◽

Cost Estimation Model ◽

The Cost

A cost model is an important tool for product design and material selection. An efficient and effective cost estimation tool is necessary for early design evaluations. In this paper, a cost estimation model is presented that estimates the production cost for metal inert gas (MIG) welded joints. This model determines the cost incurred in fabricating each joint with a detailed explanation of each cost component / driver. Each cost component has been closely analyzed and the major cost components have been included in the cost model. We used this cost model to predict the cost of the forty two different joints joined using MIG welding technique. The results predicted by the MIG welding cost model have been compared to that quoted by an expert welder. Initial results show that the cost model and the expert cost estimates follow a similar general trend. Further study is needed to refine the MIG cost model.

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