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In distributed evolutionary algorithms, migration interval is used to decidemigration moments. Nevertheless, migration moments predetermined by intervalscannot match the dynamic situation of evolution. In this paper, a scheme ofsetting the success rate of migration based on subpopulation diversity at eachinterval is proposed. With the scheme, migration still occurs at intervals, butthe probability of immigrants entering the target subpopulation will bedetermined by the diversity of this subpopulation according to a proposedformula. An analysis shows that the time consumption of our scheme isacceptable. In our experiments, the basement of parallelism is an evolutionaryalgorithm for the traveling salesman problem. Under different valuecombinations of parameters for the formula, outcomes for eight benchmarkinstances of the distributed evolutionary algorithm with the proposed schemeare compared with those of a traditional one, respectively. Results show thatthe distributed evolutionary algorithm based on our scheme has a significantadvantage on solutions especially for high difficulty instances. Moreover, itcan be seen that the algorithm with the scheme has the most outstandingperformance under three value combinations of above-mentioned parameters forthe formula.

Subpopulation Diversity Based Selecting Migration Moment in Distributed Evolutionary Algorithms