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Advanced Optimization Techniques

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Mechanical Design Optimization Using Advanced Optimization Techniques

Part of the book series: Springer Series in Advanced Manufacturing ((SSAM))

Abstract

This chapter presents the details of existing optimization algorithms such as Genetic Algorithm (GA), Artificial Immune Algorithm (AIA), Differential Evolution (DE), Biogeography-Based Optimization (BBO), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Harmony Elements Algorithm (HEA), Shuffled Frog Leaping Algorithm (SFLA) and Grenade Explosion Algorithm (GEA). The step-by-step procedure of implementation of each algorithm is presented. Some modifications made to improve the performance of PSO, ABC and HEA are also presented. In addition, four different hybrid algorithms are presented by keeping ABC as the base algorithm. The hybrid algorithms presented are: HPABC (Hybrid Particle swarm-based Artificial Bee Colony), HBABC (Hybrid Biogeography-based Artificial Bee Colony), HDABC (Hybrid Differential evolution-based Artificial Bee Colony) and HGABC (Hybrid Genetic algorithm-based Artificial Bee Colony).

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Author information

Authors and Affiliations

  1. Mechanical Engineering Department, S.V. National Institute of Technology, Ichchhanath, 395007, Surat, Gujarat, India

    Dr. R. Venkata Rao

  2. Department of Mechanical Engineering, B. H. Gardi College of Engineering and Technology, Rajkot, India

    Vimal J. Savsani

Authors
  1. Dr. R. Venkata Rao
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  2. Vimal J. Savsani
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© 2012 Springer-Verlag London

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Rao, R.V., Savsani, V.J. (2012). Advanced Optimization Techniques. In: Mechanical Design Optimization Using Advanced Optimization Techniques. Springer Series in Advanced Manufacturing. Springer, London. https://doi.org/10.1007/978-1-4471-2748-2_2

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  • DOI: https://doi.org/10.1007/978-1-4471-2748-2_2

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-2747-5

  • Online ISBN: 978-1-4471-2748-2

  • eBook Packages: EngineeringEngineering (R0)

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