S1 Dataset -

<div><p>An improved ant-lion algorithm is proposed to solve the load allocation problem to improve the efficiency of load allocation in the power system. The global search capability and optimization performance of the algorithm have been significantly improved by introducing elite weights and chaotic search mechanisms. The innovation of the research lies in not only optimizing economic goals, but also considering environmental goals, achieving dual optimization of economy and environment. The average running time of the proposed algorithm in Sphere function and Griebank function was 2.67s and 1.64s, respectively. The required number of iterations was significantly better than other algorithms. In the verification of solving economic load dispatch, the improved ant-lion optimizer achieved a total fuel cost reduction of 0.10% -2.39% and 6% in both 3-unit and 6-unit simulations, respectively, compared to the other three algorithms. In the verification of solving environmental and economic load dispatch, considering the valve point effect, this proposed optimization scheme had a total fuel cost of 622.46 $/hr and a total emission of 0.20 tons/h. The total objective function was 1542.54 $/hr, which was an average reduction of 53.55 $/hr compared to the other five algorithms. Therefore, improving the ant-lion optimizer can enhance its optimization performance. The improved ant-lion optimizer has positive application significance in power system load dispatch and can achieve superior load dispatch results.</p></div>