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[BAM16b] Optimal Multi-Crop Planning System Implemented Under Deficit Irrigation

Conférence Internationale avec comité de lecture : MELECON 2016 Conference, April 2016, Vol. 1(1), pp.1-6, Series 1, Limassol, Cyprus, (DOI: 10.1109/MELCON.2016.7495480 )

Mots clés: nonlinear pro¬gramming, simulated annealing, particle swarm optimization

Résumé: Multi-Crop planning (MCP) optimization model for cropping pattern and water allocation is introduced as a nonlinear programming problem. Its solution promotes an efficient use of water with a flexibility to keep the chosen crops at either full or deficit irrigation throughout different stages so that the net financial return is maximized within certain production bounds and resources constraints. The problem-solution approach is as follows: at first a preliminary mathematical tools are presented involving existence, benchmark linear models and a relaxation formulation, second two meta-heuristic algorithms Simulated Annealing (SA) and Particle Swarm Optimisation (PSO) are inplemented as a numerical technique for solving the MCP problem. The particularity of our approach consists of using the solution of the linear problem as an initial guess for the SA, while for PSO thé particle swarm is initiated in the neighborhood of that solution

BibTeX

@inproceedings {
BAM16b,
title="{Optimal Multi-Crop Planning System Implemented Under Deficit Irrigation}",
author=" B. BOU-FAKREDDINE and S. ABOU-CHAKRA and I. MOUGHARBEL and A. Faye and Y. Pollet ",
booktitle="{MELECON 2016 Conference}",
year=2016,
edition="1",
month="April",
series="1",
volume=1,
issue=1,
pages="1-6",
address="Limassol, Cyprus",
doi=" 10.1109/MELCON.2016.7495480 ",
}