Development of a Genetic Algorithm Based Search Strategy Suited For Design Optimisation of Internal Combustion Engines

Authors

  • N. G. Nalitolela University of Dar es Salaam
  • H. Kadete University of Dar es Salaam

DOI:

https://doi.org/10.52339/tjet.v31i1.424

Abstract

Engine design optimisation is a multi-objective, multi-domain problem in a discontinuous design space. The state of the art of optimisation techniques shows that only methods of direct and adaptive search are appropriate for this type of problem. These include, adaptive random search, simulated annealing, evolution strategies and genetic algorithms. Of
these methods, the genetic algorithms have been shown to be the most suited for the optimisation of multi-modal response functions in a discontinuous design space. This paper considers the important characteristics of genetic algorithms and their adaptation for use in parametric design optimisation of internal combustion engines. In order to verify the basic
functionality of the proposed optimisation strategy, a genetic algorithm based, optimisation software was developed and tested on a number of analytical functions, selected from optimisation literature, with satisfactory results.

Downloads

Download data is not yet available.

Author Biographies

N. G. Nalitolela, University of Dar es Salaam

Faculty of Mechanical and Chemical Engineering

H. Kadete, University of Dar es Salaam

Faculty of Mechanical and Chemical Engineering

Downloads

Published

2008-06-30

How to Cite

Nalitolela, N., & Kadete, H. (2008). Development of a Genetic Algorithm Based Search Strategy Suited For Design Optimisation of Internal Combustion Engines. Tanzania Journal of Engineering and Technology, 31(1), 127-138. https://doi.org/10.52339/tjet.v31i1.424
Abstract viewed = 96 times