An Improved Simulated Annealing Approach for Optimal Layout of Agricultural Irrigation Systems

Abstract

Efficient allocation of irrigation facilities is crucial for sustainable agricultural water management. Optimizing the layout of irrigation systems under nonlinear cost structures and discrete decision variables, however, remains a challenging combinatorial problem. This study proposes an Improved Simulated Annealing Algorithm (ISA) to optimize the static configuration of an irrigation network consisting of sprinklers, water tanks, and pipelines. The objective is to minimize total construction costs while ensuring complete irrigation coverage. The algorithm incorporates three enhancement mechanisms—memory function, reheating operation, and dual-threshold control—to enhance global search capability and convergence stability. Additionally, a Minimum Spanning Tree (MST) method is embedded to dynamically optimize pipeline topology during iterations. Experimental results on a 1-hectare farm in Changchun, Jilin Province, China, demonstrate that the ISA algorithm achieves an optimal configuration with 15 sprinklers and 10 water tanks, minimizing total construction cost while maintaining full irrigation coverage. The spatial distribution of facilities exhibits an economically rational pattern: sprinklers are concentrated near water sources, while water tanks are placed in remote areas. The proposed ISA provides a robust and scalable approach for irrigation system layout optimization and has potential applications in other agricultural network design problems.