基于图的分布式并行基因编程模型

Graph-based parallel distributed genetic programming model

基因编程(GP)算法具有天然的并行性,因此出现了并行分布式GP模型,如主从模型、岛屿模型和网格模型等。但是实现这些分布式模型的算法过程复杂,不具有可重用性,很难依据不同拓扑结构来快速实现大规模的GP计算。针对这些缺点,提出了基于图的并行分布式GP模型,形式化地描述了图中的各种GP操作,使其能够支持不同拓扑结构的GP分布式并行计算。经过实验测试,该模型能够实现上述三种GP模型,并具有稳定、高效、易实现的特点。

Since Genetic Programming （GP） is of natural parallelism, the parallel and distributed GP model was developed, including master-slave model, island model and grid model. However, the realizing algorithm of these distributed models is complex and they cannot be reused. It is difficult to achieve the scale computation of GP quickly based on different topologies. Due to these shortcomings, the authors presented the graph-based parallel distributed GP model which realizes formal description of the various operations of GP, and could support the distributed parallel computation of GP for different topologies. It is easy to achieve the master-slave model, island model and grid model of GP through experimental test. The new model is stable, efficient and easy to realize.