Parallel Genetic Algorithm

本文深入探讨了并行遗传算法(PGA)的关键概念与搜索策略,包括空间种群结构多样化、岛屿模型、随机迁移等机制。同时,文章还介绍了几种常见的选择与交叉算子,如均匀交叉和两点交叉,为理解并行遗传算法提供了全面视角。

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Parallel Genetic Algorithm(PGA)

步骤

并行遗传算法步骤

Diversitification by a spatial population structure

The island model

  • Random migration
  • Random demes

The stepping stone model

  • Discrete
  • Migration between neighboring demes
  • Demes separated in distinct population

The isolating by distance model

  • Continuous distribution
  • Demes are isolated by virtue of finite neighborhoodsof their members (根据有限邻域划分种群)
  • For mathematical convenience it is asssumed that the position of a parent at the time it gives birth relative to that of its offspring when the latter reproduces is normally distributed(考虑到数学运算的便利,假设父代相对于子代的位置是正态分布的)

Search strategy

Local hill-climbing

  • No hill-climbing
  • Next ascent hill-climbing
  • Steepest ascent hill-climbing

Selection and crossover

类比GA的算子,常见uniformly crossover 和 2-point crossover

Ref

Heinz Mühlenbein,Evolution in Time and Space – The Parallel Genetic Algorithm,Editor(s): GREGORY J.E. RAWLINS,
Foundations of Genetic Algorithms,Elsevier,Volume 1,1991
https://www.sciencedirect.com/science/article/pii/B9780080506845500239

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