  How to maintain relative high diversity is important to avoid premature
convergence in population-based optimization methods. Island model is widely
considered as a major approach to achieve this because of its flexibility and
high efficiency. The model maintains a group of sub-populations on different
islands and allows sub-populations to interact with each other via predefined
migration policies. However, current island model has some drawbacks. One is
that after a certain number of generations, different islands may retain quite
similar, converged sub-populations thereby losing diversity and decreasing
efficiency. Another drawback is that determining the number of islands to
maintain is also very challenging. Meanwhile initializing many sub-populations
increases the randomness of island model. To address these issues, we proposed
a dynamic island model~(DIM-SP) which can force each island to maintain
different sub-populations, control the number of islands dynamically and starts
with one sub-population. The proposed island model outperforms the other three
state-of-the-art island models in three baseline optimization problems
including job shop scheduler problem, travelling salesmen problem and quadratic
multiple knapsack problem.
