Energy loss optimization of run-off-road wheels applying imperialist competitive algorithm

Hamid Taghavifar, Aref Mardani

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


The novel imperialist competitive algorithm (ICA) has presented outstanding fitness on various optimization problems. Application of meta-heuristics has been a dynamic studying interest of the reliability optimization to determine idleness and reliability constituents. The application of a meta-heuristic evolutionary optimization method, imperialist competitive algorithm (ICA), for minimization of energy loss due to wheel rolling resistance in a soil bin facility equipped with single-wheel tester is discussed. The required data were collected thorough various designed experiments in the controlled soil bin environment. Local and global searching of the search space proposed that the energy loss could be reduced to the minimum amount of 15.46 J at the optimized input variable configuration of wheel load at 1.2 kN, tire inflation pressure of 296 kPa and velocity of 2 m/s. Meanwhile, genetic algorithm (GA), particle swarm optimization (PSO) and hybridized GA–PSO approaches were benchmarked among the broad spectrum of meta-heuristics to find the outperforming approach. It was deduced that, on account of the obtained results, ICA can achieve optimum configuration with superior accuracy in less required computational time.

Original languageEnglish
Pages (from-to)57-65
Number of pages9
JournalInformation Processing in Agriculture
Issue number1
Early online date30 Jun 2014
Publication statusPublished - 1 Aug 2014
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2014 China Agricultural University


  • Energy loss
  • Genetic algorithm
  • Imperialist competitive algorithm
  • Particle swarm optimization
  • Soil bin

ASJC Scopus subject areas

  • Forestry
  • Aquatic Science
  • Animal Science and Zoology
  • Agronomy and Crop Science
  • Computer Science Applications


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