On the order of variables for multitasking optimization

As an emerging paradigm in evolutionary computation, multi-tasking algorithm can solve multiple tasks simultaneously by using the hidden parallelism to transfer knowledge between tasks. Broadly speaking, in the literature, the order of variables of one task has not been explored so far. In this paper, we thus analyze the disturbed individuals and genetic mechanism in the multitasking environment with only two tasks. The experiment results on four instances revealed that, the effect of the reserve order on multi-tasking algorithm is not significant in practice.