AN OPTIMAL SILVICULTURAL REGIME MODEL USING COMPETITIVE CO-EVOLUTIONARY GENETIC ALGORITHMS

Oliver Chikumbo

2009

Abstract

A competitive co-evolutionary genetic algorithm was successfully employed to determine an optimal silvicultural regime for the South African Pinus patula Schl. Et Cham. The solution to the silvicultural regime included: initial planting density; frequency, timing and intensity of thinnings; final crop number; and rotation length. The growth dynamics for P.patula were estimated using dynamical models, the building blocks of the combined optimal control and parameter selection formulation, with a single objective function that was maximised for value production. The results were compared against a silvicultural regime determined using Pontryagin’s Maximum Principle. Both the regimes were then compared against the recommended silvicultural regime determined from years of experimental trials. The genetic algorithms regime was superior to the other two.

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Paper Citation


in Harvard Style

Chikumbo O. (2009). AN OPTIMAL SILVICULTURAL REGIME MODEL USING COMPETITIVE CO-EVOLUTIONARY GENETIC ALGORITHMS . In Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICEC, (IJCCI 2009) ISBN 978-989-674-014-6, pages 209-217. DOI: 10.5220/0002314202090217


in Bibtex Style

@conference{icec09,
author={Oliver Chikumbo},
title={AN OPTIMAL SILVICULTURAL REGIME MODEL USING COMPETITIVE CO-EVOLUTIONARY GENETIC ALGORITHMS},
booktitle={Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICEC, (IJCCI 2009)},
year={2009},
pages={209-217},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002314202090217},
isbn={978-989-674-014-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICEC, (IJCCI 2009)
TI - AN OPTIMAL SILVICULTURAL REGIME MODEL USING COMPETITIVE CO-EVOLUTIONARY GENETIC ALGORITHMS
SN - 978-989-674-014-6
AU - Chikumbo O.
PY - 2009
SP - 209
EP - 217
DO - 10.5220/0002314202090217