Compact Sine Cosine Algorithm with Multigroup and Multistrategy for Dispatching System of Public Transit Vehicles

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.

Automated summary

This paper proposes a multigroup Multistrategy Compact Sine Cosine Algorithm (MCSCA) for intelligence optimization, which achieves better optimization capability by using compact and grouping strategies. Experimental results demonstrate that MCSCA can achieve better optimization in solving dispatch system problems.