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Technical indicators and mining sequence are often optimized separately when optimizing metal mine production. This approach ignores the mutual influence between indicators and mining sequence, and the optimization results may not reach the global optimum. This study focuses on the entire production process of a metal mine and establishes a model and creates an algorithm for the simultaneous dynamic optimization of the technical indicators and mining sequence of a metal mine. A model of the dynamic relationships between technical indicators is initially created in order to derive an optimization model that dynamically optimizes both the technical indicators and the mining sequence of a metal mine. A hybrid coding AADE algorithm is developed to solve the optimization equation. A test case of the Huogeqi copper mine is presented to demonstrate the use of the model and the algorithm. The simultaneous dynamic optimization of technical indicators and mining sequence produced greater NPV in the test case than the optimization of technical indicators alone; NPV increased by 1161.01 10 4  CNY. In addition, the hybrid coding AADE algorithm was compared with hybrid coding GA, DE and ADE algorithms. The hybrid coding AADE algorithm performed searches significantly better than the other three hybrid coding algorithms in solving the simultaneous dynamic optimization for technical indicators and mining sequence.

Simultaneous Dynamic Optimization of Technical Indicators and Mining Sequence in Metal Mines Using Hybrid Coding AADE