On the genetic programming of time-series predictors for supply chain management

  title={On the genetic programming of time-series predictors for supply chain management},
  author={Alexandros Agapitos and Matthew Dyson and Jenya Kovalchuk and Simon M. Lucas},
Single and multi-step time-series predictors were evolved for forecasting minimum bidding prices in a simulated supply chain management scenario. Evolved programs were allowed to use primitives that facilitate the statistical analysis of historical data. An investigation of the relationships between the use of such primitives and the induction of both accurate and predictive solutions was made, with the statistics calculated based on three input data transformation methods: integral… CONTINUE READING
Highly Cited
This paper has 20 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.
10 Citations
2 References
Similar Papers


Publications citing this paper.
Showing 1-10 of 10 extracted citations


Publications referenced by this paper.
Showing 1-2 of 2 references

Genetic programming polynomial models of financial data series

  • H. Iba, N. Nikolaev
  • In Proceedings of the IEEE
  • 2000
Highly Influential
8 Excerpts

Similar Papers

Loading similar papers…