SciELO - Scientific Electronic Library Online

 
vol.23 issue2Reconfigurable product routing and control for mass customisation manufacturingHow to control process variability more effectively: The case of a B-complex vitamin production process author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Article

Indicators

Related links

  • On index processCited by Google
  • On index processSimilars in Google

Share


South African Journal of Industrial Engineering

On-line version ISSN 2224-7890
Print version ISSN 1012-277X

Abstract

RADMEHR, F.  and  GHARNEH, N.S.. Forecasting method based on high order fuzzy time series and simulated annealing technique. S. Afr. J. Ind. Eng. [online]. 2012, vol.23, n.2, pp.176-190. ISSN 2224-7890.

This paper proposes a fuzzy forecasting problem to forecast the Alabama University enrolment dataset. A novel simulated annealing heuristic algorithm is used to promote the accuracy of forecasting. The algorithm enjoys two new neighbourhood search operators called 'subtitle' and 'adjust'. A Taguchi method is also used as an optimisation technique to tune the different parameters and operators of the proposed model comprehensively. The experimental results show that the proposed model is more accurate than existing models.

        · abstract in Afrikaans     · text in English     · English ( pdf )

 

Creative Commons License All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License