This paper studies the problem of intelligence optimization, a fundamental problem in analyzing the optimal solution in a wide spectrum of applications such as transportation and wireless sensor network (WSN). To achieve better optimization capability, we propose a multigroup Multistrategy Compact Sine Cosine Algorithm (MCSCA) by using the compact strategy and grouping strategy, which makes the initialized randomly generated value no longer an individual in the population and avoids falling into the local optimum. New evolution formulas are proposed for the intergroup communication strategy. Performance studies on the CEC2013 benchmark demonstrate the effectiveness of our new approach regarding convergence speed and accuracy. Finally, we apply MCSCA to solve the dispatch system of public transit vehicles. Experimental results show that MCSCA can achieve better optimization.

中文翻译：

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紧凑型多组多策略正弦余弦算法在公交车辆调度系统中的应用

本文研究智能优化问题，这是分析交通运输和无线传感器网络（WSN）等广泛应用中的最佳解决方案的基本问题。为了获得更好的优化能力，我们通过使用紧凑策略和分组策略提出了一种多组多策略紧凑正弦余弦算法（MCSCA），它使初始化后的随机生成的值不再是总体中的一个个体，并且避免陷入局部最优状态。提出了群体间交流策略的新进化公式。根据CEC2013基准进行的性能研究证明了我们的新方法在收敛速度和准确性方面的有效性。最后，我们运用MCSCA来解决公交车辆的调度系统。