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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

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Published on: December 9, 2012

Mine water cooperative optimal scheduling based on improved genetic algorithm.

Yang Liu¹, Zihang Zhang¹, Dongxu Zhu²

¹School of Mechanical Electronic & Information Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China.

|March 21, 2024

Summary

This study introduces an optimized scheduling strategy for mine water reuse, significantly cutting recovery costs and time in coal mine shafts. The new approach enhances water resource management efficiency in mining operations.

Keywords:

Cooperative scheduling Improved genetic algorithm Mine water Reuse cost

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Area of Science:

Mining Engineering
Water Resource Management
Optimization Algorithms

Background:

Coal mine shafts face challenges with inefficient water scheduling and high operational costs.
Effective management of mine water resources is crucial for sustainability and economic viability.

Purpose of the Study:

To develop a hierarchical optimization scheduling strategy for mine water reuse.
To minimize both the cost and maximize the reuse efficiency of mine water resources.
To address limitations of traditional genetic algorithms in optimization problems.

Main Methods:

A hierarchical optimization scheduling strategy was designed using Inner Mongolia mining data.
Objective functions were formulated for maximum reuse efficiency and minimum cost, with water quality and quantity constraints.
An improved adaptive autobiographical operator, based on simulated annealing, was developed to overcome local optima in genetic algorithms.

Main Results:

The improved algorithm reduced monthly recovery costs by 10.34% (66,779.36 CNY) in the heating season and 9.91% (61,469.28 CNY) in the non-heating season.
Monthly recovery time decreased by 136.99 hours in the heating season and 154.52 hours in the non-heating season.
The strategy demonstrated significant reductions in both cost and time for mine water recovery.

Conclusions:

The proposed hierarchical optimization scheduling strategy effectively reduces mine water recovery costs and time.
The integration of simulated annealing principles enhances the performance of optimization algorithms for mine water management.
This approach offers a practical solution for improving the economic and operational efficiency of coal mine water resource utilization.