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Weight Minimization of a Speed Reducer Using Prey Predator Algorithm

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  • Surafel Luleseged Tilahun

    (Department of Mathematical Sciences, University of Zululand, KwaDlangeZwa, South Africa)

  • Maba B. Matadi

    (Department of Mathematical Sciences, University of Zululand, KwaDlangeZwa, South Africa)

Abstract

This article describes how a speed reducer is a mechanical device which is very useful to reduce speed in different machineries. The use of gears to adjust a speed is an old practice, however the formulation of the problem as an optimization problem and solving it using different approaches begun in early 1970's. The problem is a constrained, nonlinear and nonconvex problem. That makes it challenging to handle it by deterministic approaches. Hence, different metaheuristic and hybrid methods have been proposed and used. Furthermore, due to the challenging behaviour of the problem, it has been used as a benchmark problem to test and compare new algorithms. In this article, a brief review of the problem, its application and the advances in solving the problem will be presented. A metaheuristic algorithm called prey predator algorithm will then be used to solve the problem. Prey-predator algorithm has been found to be effective with an easy way to control the exploration and exploitation search behaviour. Simulation-based comparison with previous results shows that indeed the algorithm produces a promising result. Hence, this study showed that applying prey predator algorithm for speed reducer production is a reasonable idea.

Suggested Citation

  • Surafel Luleseged Tilahun & Maba B. Matadi, 2018. "Weight Minimization of a Speed Reducer Using Prey Predator Algorithm," International Journal of Manufacturing, Materials, and Mechanical Engineering (IJMMME), IGI Global, vol. 8(2), pages 19-32, April.
  • Handle: RePEc:igg:jmmme0:v:8:y:2018:i:2:p:19-32
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    Cited by:

    1. Surafel Luleseged Tilahun & Mohamed A. Tawhid, 2019. "Swarm hyperheuristic framework," Journal of Heuristics, Springer, vol. 25(4), pages 809-836, October.

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