本文基于遗传微粒群算法(Genetic ParticleSwarm Opti mization,GPSO),结合2-opt启发式算法设计混合遗传微粒群算法求解TSP问题(Hybrid Genetic Par...
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...在对标准微粒群算法模型及其机理进行分析的基础上,提出了一种广义微粒群算法模型(Generalized Particle Swarm Optimization,GPSO).该模型的微粒进化方程具有满足一定条件的抽象形式.
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以上来源于: WordNet
The experimental results demonstrate that GPSO algorithm has obvious optimization effect in solving TSP.
实验结果表明，GPSO算法在求解旅行商问题上，优化效果明显。
At each iteration, GPSO can obtain the inertia weight auto-adapted to help the algorithm overcome precocious shortcoming effectively.
GPSO可在每次迭代中自适应地得到惯性权重，有效帮助算法克服了早熟的缺点。
Relative to the ACO algorithm, GPSO algorithm is better than the ACO algorithm whether in the search speed, search precision, or in the algorithm running time.
相对于蚁群算法来说，不论是在搜索速度、搜索精度，还是在算法的运行时间上，GPSO算法都要优于蚁群算法。
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