Resumen
Research on tree-type irrigation pipe networks is an important component of agricultural water-saving projects. The optimal design of tree-type irrigation pipe networks is a key aspect regarding the profitability of irrigated agriculture. Meanwhile, swarm intelligence optimization algorithms have good computational ability and can be applied to solve many optimization problems in agricultural engineering. To identify the lowest investment cost for a pipe network, this study defined the concept of an upper water node to ensure the connectivity of tree-type irrigation pipe networks, and therefore, improve the pipe network planning model without using preliminary network connection diagrams. In addition, this study proposed an improved chicken swarm optimization algorithm (Improved Chicken Swarm Optimization using Adaptive Search and Variation, ICSO-ASV), which was applied to solve 12 test functions of different dimensions. The test results show that, compared to the traditional chicken swarm algorithm and other algorithms in the control group, the ICSO-ASV algorithm could effectively improve the global search capability. Finally, the ICSO-ASV algorithm was used to plan and design 15-node and 40-node pipe networks. The calculation results show that the average investment costs of the two pipe networks generated by the ICSO-ASV algorithm were 42.20% and 31.09% lower than those generated by the traditional chicken swarm algorithm, which further verified the feasibility of applying ICSO-ASV to design tree-type irrigation pipe networks. Thus, the design method proposed in this study can solve the optimal problems of tree-type irrigation pipe networks with varying topologies. The optimal solutions can be generated automatically using the ICSO-ASV algorithm if essential parameters of the pipe network planning model are provided.