Meta-Heuristic Structure for Multiobjective Optimization Case Study: Green Sand Mould System

View Sample PDF

Author(s): T. Ganesan (Universiti Technologi PETRONAS, Malaysia), I. Elamvazuthi (Universiti Technologi PETRONAS, Malaysia), K. Z. KuShaari (Universiti Technologi PETRONAS, Malaysia)and P. Vasant (Universiti Technologi PETRONAS, Malaysia)
Copyright: 2014
Pages: 21
Source title: Smart Manufacturing Innovation and Transformation: Interconnection and Intelligence
Source Author(s)/Editor(s): ZongWei Luo (The University of Hong Kong, China)
DOI: 10.4018/978-1-4666-5836-3.ch003

Keywords: Artificial Intelligence / Business Science Reference / Computer Science & IT / Industrial Informatics

Purchase

View Meta-Heuristic Structure for Multiobjective Optimization Case Study: Green Sand Mould System on the publisher's website for pricing and purchasing information.

Abstract

In engineering optimization, one often encounters scenarios that are multiobjective (MO) where each of the objectives covers different aspects of the problem. It is hence critical for the engineer to have multiple solution choices before selecting of the best solution. In this chapter, an approach that merges meta-heuristic algorithms with the weighted sum method is introduced. Analysis on the solution set produced by these algorithms is carried out using performance metrics. By these procedures, a novel chaos-based metaheuristic algorithm, the Chaotic Particle Swarm (Ch-PSO) is developed. This method is then used generate highly diverse and optimal solutions to the green sand mould system which is a real-world problem. Some comparative analyses are then carried out with the algorithms developed and employed in this work. Analysis on the performance as well as the quality of the solutions produced by the algorithms is presented in this chapter.

The IRMA Community

Research IRM

Meta-Heuristic Structure for Multiobjective Optimization Case Study: Green Sand Mould System

Purchase

Abstract

Related Content

IRMA Sponsors