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Metaheuristic Approaches for Extrusion Manufacturing Process: Utilization of Flower Pollination Algorithm and Particle Swarm Optimization

Metaheuristic Approaches for Extrusion Manufacturing Process: Utilization of Flower Pollination Algorithm and Particle Swarm Optimization
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Author(s): Pauline Ong (Universiti Tun Hussein Onn Malaysia (UTHM), Malaysia), Desmond Daniel Vui Sheng Chin (Universiti Tun Hussein Onn Malaysia (UTHM), Malaysia), Choon Sin Ho (Universiti Tun Hussein Onn Malaysia (UTHM), Malaysia) and Chuan Huat Ng (Universiti Tun Hussein Onn Malaysia (UTHM), Malaysia)
Copyright: 2018
Pages: 14
Source title: Handbook of Research on Applied Optimization Methodologies in Manufacturing Systems
Source Author(s)/Editor(s): Ömer Faruk Yılmaz (Istanbul Technical University, Turkey & Yalova University, Turkey) and Süleyman Tüfekçí (University of Florida, USA)
DOI: 10.4018/978-1-5225-2944-6.ch003

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Abstract

Optimization, basically, is a method used to find solutions for a particular problem without neglecting the existing boundaries or limitations. Flower Pollination Algorithm (FPA) is one of the recently developed nature inspired algorithms, based on the intriguing process of flower pollination in the world of nature. The main aim of this study is to utilize FPA in optimizing cold forward extrusion process in order to obtain optimal parameters to produce workpiece with the minimum force load. It is very important to find the most optimal parameters for an extrusion process in order to prevent waste from happening due to trial and error method in determining the optimal parameters and thus, FPA is used to replace the traditional trial and error method to optimize the cold forward extrusion process. The optimization performance of the FPA is then compared with the particle swarm optimization (PSO), in which the FPA shows comparable performance in this regard.

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