Int. J. Simul. Multidisci. Des. Optim.
Volume 9, 2018
|Number of page(s)||6|
|Published online||16 March 2018|
Irrigation water allocation optimization using multi-objective evolutionary algorithm (MOEA) − a review
Department of Applied Mathematics and Computational Sciences, Nelson Mandela African Institution of Science Technology,
P.O. Box 447,
2 Department of Mathematics, College of Natural and Applied Science, University of Dar es Salaam, P.O. Box 35062, Dar es Salaam, Tanzania
* e-mail: firstname.lastname@example.org
Accepted: 10 January 2018
This paper analyzes more than 40 papers with a restricted area of application of Multi-Objective Genetic Algorithm, Non-Dominated Sorting Genetic Algorithm-II and Multi-Objective Differential Evolution (MODE) to solve the multi-objective problem in agricultural water management. The paper focused on different application aspects which include water allocation, irrigation planning, crop pattern and allocation of available land. The performance and results of these techniques are discussed. The review finds that there is a potential to use MODE to analyzed the multi-objective problem, the application is more significance due to its advantage of being simple and powerful technique than any Evolutionary Algorithm. The paper concludes with the hopeful new trend of research that demand effective use of MODE; inclusion of benefits derived from farm byproducts and production costs into the model.
Key words: Multi-objective / irrigation / pareto set / evolutionary algorithm
© I.M. Fanuel et al., published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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