The gravitational search algorithm (GSA) is a novel optimization technique that relies upon the law of motion and law of gravity of masses to describe the interaction between the agents. The GSA has shown outstanding performance but suffers from the drawback of a slow process due to the dependence of the fitness function on the masses of the agents. As a result, after each iteration, the masses get heavier, restricting their movement. Due to this effect, the masses cancel out the gravitational forces on each other, preventing them from finding the optimum quickly. To overcome this limitation, an improved GSA based on a modified exploitation strategy is proposed herein. The primary aim of this modification is to enhance the performance of the algorithm in terms of faster convergence and avoidance of premature convergence. An electromagnetic optimization problem is used to validate the performance of the presented method. The simulation results confirm that the proposed method provides outstanding results in solving Loney’s solenoid design problem and that the stability of the solution is much better compared with those obtained using the standard gravitational search algorithm or various other state-of-the-art techniques that have previously been applied to solve this problem.

中文翻译：

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一种解决电磁设计问题的改进引力搜索算法

引力搜索算法（GSA）是一种新颖的优化技术，它依靠运动定律和质量引力定律来描述主体之间的相互作用。GSA已显示出出色的性能，但由于适应性功能对试剂质量的依赖性而遭受流程缓慢的缺点。结果，在每次迭代之后，群众变得更重，限制了他们的运动。由于这种作用，质量块抵消了彼此的重力，从而阻止了它们快速找到最佳位置。为了克服该限制，本文提出了基于改进的利用策略的改进的GSA。此修改的主要目的是在更快的收敛速度和避免过早收敛的方面增强算法的性能。电磁优化问题用于验证所提出方法的性能。仿真结果证实，所提出的方法在解决Loney螺线管设计问题方面提供了出色的结果，并且与使用标准重力搜索算法或其他各种具有以下技术的最新技术获得的解决方案相比，该解决方案的稳定性要好得多：以前曾被用来解决这个问题。