Two Meta-Heuristics for Solving Unconstrained Optimization Problems and Machinery Problems

Abstract:

Machining optimization problem aims to optimize machinery conditions which are important for economic settings. The effective methods for solving these problems using a finite sequence of instructions can be categorized into two groups; exact optimization algorithm and meta-heuristic algorithms. A well-known meta-heuristic approach called Harmony Search Algorithm was used to compare with Particle Swarm Optimization. We implemented and analysed algorithms using unconstrained problems under different conditions included single, multi-peak, curved ridge optimization, and machinery optimization problem. The computational outputs demonstrated the proposed Particle Swarm Optimization resulted in the better outcomes in term of mean and variance of process yields.

• Periodical: Advanced Materials Research (Volumes 1044-1045)
• Pages: 1418-1423
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.1044-1045.1418
• Online since: October 2014
• Authors: Pasura Aungkulanon*
• Keywords: Harmony Search Algorithm, Machinery Problems, Meta-Heuristics Algorithms, Optimization, Particle Swarm Optimization (PSO)

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