Irrigation water allocation optimization using Multi-Objective Evolutionary Algorithm (MOEA): A review
| dc.contributor.author | Fanuel, Ibrahim Mwita | |
| dc.contributor.author | Mushi, Allen R. | |
| dc.contributor.author | Kajunguri, Damian | |
| dc.date.accessioned | 2024-04-15T09:52:57Z | |
| dc.date.available | 2024-04-15T09:52:57Z | |
| dc.date.issued | 2018 | |
| dc.description | Article published by EDP Sciences in the International Journal for Simulation and Multidisciplinary Design Optimization, Volume 9, Pages A3 | |
| dc.description.abstract | 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. | |
| dc.description.sponsorship | Private | |
| dc.identifier.citation | APA | |
| dc.identifier.uri | https://doi.org/10.1051/smdo/2018001 | |
| dc.identifier.uri | https://scholar.mzumbe.ac.tz/handle/123456789/601 | |
| dc.language.iso | en | |
| dc.publisher | EDP Sciences | |
| dc.subject | Multi-objective | |
| dc.subject | irrigation | |
| dc.subject | pareto set | |
| dc.subject | evolutionary algorithm | |
| dc.title | Irrigation water allocation optimization using Multi-Objective Evolutionary Algorithm (MOEA): A review | |
| dc.type | Article |