A combined simulation–genetic algorithm optimization model for optimal rule curves of a reservoir: a case study of the Nam Oon Irrigation Project, Thailand

2007 ◽  
Vol 21 (23) ◽  
pp. 3211-3225 ◽  
Author(s):  
Watchara Suiadee ◽  
Tawatchai Tingsanchali
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
Optimal Rule ◽  
Irrigation Project ◽  
Rule Curves ◽  
Combined Simulation

scholarly journals Optimum sizing of cogeneration plants by means of a genetic algorithm optimization: A case study

2019 ◽  
Vol 15 ◽  
pp. 100525 ◽  
Author(s):  
M.A. Ancona ◽  
M. Bianchi ◽  
C. Biserni ◽  
F. Melino ◽  
S. Salvigni ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization

scholarly journals Development of a Genetic Algorithm Optimization Model for Biogas Power Electrical Generation

2019 ◽  
Vol 4 (2) ◽  
pp. 7-11 ◽  
Author(s):  
Timothy Oluwaseun Araoye ◽  
C. A. Mgbachi ◽  
Olushola Adebiyi Omosebi ◽  
Oluwaseun Damilola Ajayi ◽  
Adeleye Qasim Olaniyan
Keyword(s):  
Genetic Algorithm ◽  
Power Generation ◽  
Optimization Model ◽  
Electrical Power ◽  
Power Production ◽  
Algorithm Optimization ◽  
Rotating Shaft ◽  
Genetic Algorithm Optimization ◽  
Animal Dung ◽  
Electrical Generation

Biogas power generation is renewable energy made from biological materials. Biogas power production is technology which helps in development of sustainable energy supply systems. This paper develops Genetic Algorithm optimization model for Biogas electrical power generation of Ilora in Oyo, Oyo state. The production is done using co-digestion system of pig dung and Poultry dung under the process of anaerobic digestion. The pig dung and poultry dung were mixed 50:50%. MATLAB and VISUAL BASIC Software was used to carry out simulations to develop optimized Genetic Algorithm model for Biogas power production with aims to improving electricity accessibility and durability of the community. The results of the research reveal the Empirical Biogas power production without and with Genetic Algorithm optimization. The Result showed that biogas electrical power generated without and with Genetic Algorithm Optimization were 5KW and 11.18KW respectively. The biogas power generation was increased by 6.18KW, which is 38.2% increase after Genetic Algorithm optimization. The results show the application of the Genetic Algorithm optimization model which can be used to improving Biogas power generation when amount of methane gas produced from the animal dung varies with speed of thermal rotating shaft.

A SIMPLIFIED MULTI-OBJECTIVE GENETIC ALGORITHM OPTIMIZATION MODEL FOR CANAL SCHEDULING

2011 ◽  
Vol 61 (3) ◽  
pp. 294-305 ◽  
Author(s):  
S. Z. Peng ◽  
Y. Wang ◽  
S. Khan ◽  
T. Rana ◽  
Y. F. Luo
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm

GIS-based genetic algorithm optimization tool for supporting land use and land management restructuring

2007 ◽  
Vol 13 (1s) ◽  
pp. 33-37
Author(s):  
V. Makarenko ◽  
◽  
G. Ruecker ◽  
R. Sommer ◽  
N. Djanibekov ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Land Use ◽  
Land Management ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization
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