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A platform for research: civil engineering, architecture and urbanism
WASPAS Application and Evolutionary Algorithm Benchmarking in Optimal Reservoir Optimization Problems
AbstractThis study applies a recently developed evolutionary algorithm (EA) called state of matter search (SMS) to minimize the total energy deficit in the Karun4 reservoir, Iran. The operation of the Karun4 reservoir is influenced by several factors, which requires a multiple criteria framework for selecting the most suitable solution EA. Five EAs, in addition to the SMS, were evaluated for the reservoir operation problem on the basis of four performance criteria and the fitness function (FF) value. The priority assessment on the basis of FF value revealed that the SMS outperformed the other EAs in converging to the optimal solution. However, judged by the other four performance criteria, based on weighted aggregates sum product assessment (WASPAS) technique, particle swarm optimization (PSO) proved superior to the other EAs. This paper’s results show that the selection of a solution EA for solving complex reservoir optimization problem requires a multicriteria decision-making process. Multiobjective evolutionary algorithms (MOEAs) are well-suited for the task.
WASPAS Application and Evolutionary Algorithm Benchmarking in Optimal Reservoir Optimization Problems
AbstractThis study applies a recently developed evolutionary algorithm (EA) called state of matter search (SMS) to minimize the total energy deficit in the Karun4 reservoir, Iran. The operation of the Karun4 reservoir is influenced by several factors, which requires a multiple criteria framework for selecting the most suitable solution EA. Five EAs, in addition to the SMS, were evaluated for the reservoir operation problem on the basis of four performance criteria and the fitness function (FF) value. The priority assessment on the basis of FF value revealed that the SMS outperformed the other EAs in converging to the optimal solution. However, judged by the other four performance criteria, based on weighted aggregates sum product assessment (WASPAS) technique, particle swarm optimization (PSO) proved superior to the other EAs. This paper’s results show that the selection of a solution EA for solving complex reservoir optimization problem requires a multicriteria decision-making process. Multiobjective evolutionary algorithms (MOEAs) are well-suited for the task.
WASPAS Application and Evolutionary Algorithm Benchmarking in Optimal Reservoir Optimization Problems
2016
Article (Journal)
English
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| Springer Verlag | 2016