A hybrid water cycle-particle swarm optimization for solving the fuzzy underground water confined steady flow

Elsayed Metwalli Badr, Horia Elgendy

Abstract


Groundwater sustainability is the development and use of groundwater resources to meet current and future beneficial uses without causing unacceptable environmental or socioeconomic consequences. This study is the first time to apply the hybrid optimization technique for solving of managing underground water aquifers, the confined steady flow problems, where a hybrid water cycle - particle swarm optimization WCA-PSO is proposed. In particular, we introduce a novel hybrid algorithm using water cycle algorithm (WCA) and particle swarm Optimization (PSO). The performance of the novel hybrid algorithm WCA-PSO is evaluated to solve 10 benchmark problems chosen from literature. The simulation results and comparison with pure WCA and PSO algorithms confirm the effectiveness of the proposed algorithm WCA-PSO for solving various benchmark optimization functions. Finally, we solve the problem of managing underground water aquifers by WCA, PSO and the hybrid optimization WCA-PSO. The experimental results analysis and statistical tests prove that the hybrid algorithm WCA-PSO overcomes the pure algorithms.

Keywords


Water cycle algorithm; Particle swarm algorithm; Hybrid optimization; Benchmark problems; Fuzzy Multiobjective programming; Confined steady underground flow

Full Text:

PDF


DOI: http://doi.org/10.11591/ijeecs.v19.i1.pp492-504

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

shopify stats IJEECS visitor statistics