A compact compound sinusoidal differential evolution algorithm for solving optimisation problems in memory-constrained environments

In this paper, a new compact algorithm is proposed. Two sinusoidal formulas are used to automatically adjust the crossover rate and the mutation scaling factor in the compact Differential Evolution (cDE) metaheuristic. The proposed algorithm, called Compound Sinusoidal cDE, CScDE, is compared to seven state-of-the-art compact algorithms on the well-known BBOB test-bed, the CEC-2014 test suite for continuous optimisation, as well as five real-world optimisation problems chosen from the CEC-2011 benchmarks. The CScDE algorithm outperformed its competitors for most problem categories and over most dimensions. It is also compared to some well-established population-based metaheuristics.

Automated summary

A new compact algorithm, Compound Sinusoidal cDE (CScDE), is proposed in this paper, which outperforms seven state-of-the-art compact algorithms on various test beds and real-world optimization problems.