"优化算法研究：类电磁机制新进展与应用"

c mechanism algorithm (referred to as EM algorithm) is a new type of population-based heuristic algorithm proposed by Birbil and Fang in 2002, inspired by the repulsive and attractive effects between charged particles in an electromagnetic field. Its idea is to simulate the repulsion and attraction mechanism between charged particles in an electromagnetic field, and through certain criteria, make each particle move towards the optimal solution, thus finding the optimal solution to the problem. This article introduces the class electromagnetic mechanism algorithm, improves the local search method of the algorithm based on its basic framework, redefines the formula for calculating the total force, and introduces a mutation operator to accelerate the convergence of the algorithm. According to the numerical experimental results of the standard test functions, these improvements speed up the optimization speed of the algorithm without affecting the results, and improve the optimization efficiency of the algorithm. In addition, for general constrained optimization problems, the maximum entropy method is used to simplify the constraints, and a penalty function is designed to transform it into an unconstrained problem. Then, the improved class electromagnetic algorithm is used to optimize the constrained optimization standard test problems, and satisfactory results are obtained, indicating that the improved class electromagnetic mechanism algorithm can also be used to solve optimization problems under general constraints. 实验结果表明，EM算法是一种有效的优化算法。对比标准测试问题，改进后的算法在寻优速度和效率上都有所提高，并且对于一般的约束优化问题，也具有一定的适用性。因此，在优化领域中，EM算法具有重要的应用前景。 关键词：类电磁机制算法，优化算法，极大熵方法。 总的来说，EM算法是一种基于电磁场的启发式优化算法，通过模拟带电粒子之间的排斥和吸引机制，来寻找问题的最优解。本文介绍了对EM算法的改进，并对其在约束优化问题上的应用进行了探讨。研究表明，改进后的EM算法在寻优速度和效率上都有所提高，并且具有一定的适用性。因此，EM算法在实际应用中具有广泛的应用前景。