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Water Allocation Optimization and Environmental Planning with Simulated Annealing Algorithms

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  • Dongling Cheng
  • Leipo Liu

Abstract

Because of the continuous deterioration of water environment, it is ensured that the basic water demand of ecological environment is the key task of water resources utilization and control in China. In view of the uneven distribution of domestic water resources “more in the South and less in the north, more in the East and less in the west,†it is very necessary to optimize the allocation of water resources. This paper aims to optimize the allocation of water resources through simulated annealing algorithm (SAA), hoping to optimize the allocation of water resources through diversion, water intake, and storage measures such as pipelines. Based on this, this paper proposes an improved SAA pipeline construction algorithm. Aiming at the distribution of water sources in the Yangtze River Basin, the algorithm is used to optimize the objective function path to solve the unbalanced problem of rich and lack of regional water resources. And after optimizing the annealing simulation algorithm, the simulation optimization ability is significantly improved. Experiments show that the improved SAA can improve the optimal configuration by more than 50% and up to 96%, indicating that the improved algorithm has a more stable optimization planning function for the optimization of objectives and can often get a more perfect route.

Suggested Citation

  • Dongling Cheng & Leipo Liu, 2022. "Water Allocation Optimization and Environmental Planning with Simulated Annealing Algorithms," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-11, May.
  • Handle: RePEc:hin:jnlmpe:2281856
    DOI: 10.1155/2022/2281856
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    Cited by:

    1. Horng, Shih-Cheng & Lin, Shieh-Shing, 2024. "Advanced golden jackal optimization for solving the constrained integer stochastic optimization problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 217(C), pages 188-201.
    2. Shih-Cheng Horng & Shieh-Shing Lin, 2023. "Improved Beluga Whale Optimization for Solving the Simulation Optimization Problems with Stochastic Constraints," Mathematics, MDPI, vol. 11(8), pages 1-17, April.

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