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Particle swarm optimization (PSO) for CNC route problem

Nur Azia Azwani, Ismail (2002) Particle swarm optimization (PSO) for CNC route problem. Faculty of Electrical & Electronics Engineering , Universiti Malaysia Pahang.

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Abstract

The purpose of this study is to develop the application of Particle Swarm Optimization (PSO) which applicable to CNC machine route problem. In this project, the problem of CNC machine can be identifying by routing problem which it become more complicated to solve without use of any optimization method. The mathematical equation become more complexes and it will be difficult to solve using manual calculation without any optimization technique or algorithm in this project. We often see many of the method of Genetic Algorithm (GA), Ant Colony Optimization (ACO), Simulated Annealing Algorithm (SAA) and PSO are used for any optimization problems. Basically, this project is mainly concerned on Particle Swarm Optimization (PS 0) to optimize the routing of CNC machine. The algorithm used in this project is the Global Best (gbest) algorithm where it is a basic algorithm of Particle Swarm Optimization which applicable the shortest time and path of CNC machine to complete the process of drilling. In addition, the software Microsoft Visual Basic 6.0 has been used which is provide a graphic user interface (GUI) for the user to determine the coordinate of holes (particles) and desired parameters at the search space given. The user can also monitor the result and performance of the system through this software. This software will optimize the result which is to determine the path and time to complete the drilling process. In t the end of this project, it can be concluded that the Particle Swarm Optimization (PSO) method can be used and available to apply in the CNC Route Problem.

Item Type: Undergraduates Project Papers
Additional Information: Project paper (Bachelor of Electrical Engineering (Electronics)) -- Universiti Malaysia Pahang - 2012
Uncontrolled Keywords: Pattern recognition systems Swarm intelligence
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: nurudin nasir
Date Deposited: 11 Aug 2014 01:27
Last Modified: 03 Mar 2015 09:29
URI: http://umpir.ump.edu.my/id/eprint/6337
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