模拟退火生成多初始种群的遗传规划

2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA) Pub Date : 2013-07-13 DOI:10.1109/IWCIA.2013.6624797

Takuya Mototsuka, Akira Hara, J. Kushida, T. Takahama

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引用次数: 1

摘要

遗传规划(GP)和模拟退火规划(SAP)是典型的自动规划元启发式方法。本文提出了一种结合GP和SAP的并行遗传退火规划(P-GAP)方法。在P-GAP中，由SAP生成多个初始种群，各种群通过并行GP进化。随着一代的发展，人口逐渐融合。为了检验P-GAP方法的有效性，我们在五个测试问题中将P-GAP方法与常规方法进行了比较。结果表明，P-GAP的性能优于GP和SAP。

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Genetic programming with multiple initial populations generated by simulated annealing

Genetic Programming (GP) and Simulated Annealing Programming (SAP) are typical metaheuristic methods for automatic programming. We propose a new method, Parallel - Genetic and Annealing Programming (P-GAP) which combines GP and SAP. In P-GAP, multiple initial populations are generated by SAP. Respective populations evolve by parallel GP. As the generation proceeds, populations are integrated gradually. To examine the effectiveness, we compared P-GAP with the conventional methods in five test problems. As a result, P-GAP showed better performance than GP and SAP.

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2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA)

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