Subpopulation Diversity Based Accepting Immigrant in Distributed Evolutionary Algorithms

As a popular type of parallel evolutionary algorithms, distributed evolutionary algorithms (DEAs) are widely used in a variety of fields. To get better solutions of concrete problems, a scheme of subpopulation diversity based accepting immigrant in DEAs is proposed in this paper. In migration with this scheme, an immigrant will be put into its target subpopulation only if its current diversity is lower than a threshold value. Algorithm analysis shows that the extra cost of time for this scheme is acceptable in many DEAs. Experiments are conducted on instances of the Traveling Salesman Problem from the TSPLIB. Results show that the DEA based on the proposed scheme can get better solutions than the one without it.