Optimizing channel cross-section based on cat swarm optimization

Optimal design of channel cross-section is an important task in the hydraulic design of open channels. The traditional methods and models which neglect the frost heave are trial procedures and may result in failure of channels in design of irrigation channels. To improve the total cost, reliability and effectiveness, the model which is used in this study, is not only minimizing the cost of land acquisition but also the cost of concrete lining considering cost as the objective function. The constrained optimization model which considers values of thickness of channel concrete slab constraint simultaneously along with the objective of minimization of cost is propounded and solved using a recent global optimization technique, namely cat swarm optimization (CSO). The optimized channel section not only satisfies the optimal hydraulic cross-section but guarantees the safety and stability of the side walls so that both the amount of the concrete lining and the land acquisition are optimized. Finally, we take a main channel of Qinghe Irrigated Area of Farm 853 in Heilongjiang Province as a study area. The results obtained using the CSO approach are satisfaction and the method can be used for reliable design of artificial open channels. Furthermore, we compare the CSO algorithm with a genetic algorithm (GA) and the particle swarm optimization (PSO) to verify the effectiveness of the cat swarm algorithm in the channel section optimization.