贡品算法:考虑合作区域社区的进化目标优化计算

Ziyang Weng, Shuhao Wang
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摘要

本文考虑不同国家和地区在历史进程中的客观演化目标,结合复杂的外交关系和深层次的贸易合作需求,提出了一种基于合作机制的区域共同体演化算法。我们首先将区域合作描述为一个基于多元智能的复杂系统;然后,为了避免算法过早成熟而陷入局部最优解,我们引入了精英探索机制来促进区域发展;其次,提出了基于信任关系的合作判别机制;最后,通过求解速度快、求解精度高的研究案例验证了算法的有效性。实验结果表明,与弱肉强食的丛林法则不同,互利开放策略更有利于区域个体的共同进化。本文能较好地表征多智能节点之间关系的复杂网络,为复杂系统的智能决策提供参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Tribute Algorithm: Calculation of Evolutionary Goal Optimization Considering Cooperative Regional Communities
This paper proposes an evolutionary algorithm for regional communities based on cooperation mechanisms, taking into account the objective evolutionary goals of different countries and regions in historical processes, combined with the complex diplomatic relations and deep trade cooperation needs. We first represent regional cooperation as a complex system based on multiple intelligences; then, to avoid the algorithm from maturing prematurely and falling into local optimal solutions, we introduce an elite exploration mechanism to promote regional development; secondly, we propose a cooperative discriminative mechanism based on trust relationship; finally, we verify the effectiveness of the algorithm using research cases with fast solution speed and high solution accuracy. The experimental results show that, unlike the law of the jungle of the weak and the strong, the mutually beneficial open strategy is more conducive to the coevolution of regional individuals. This paper can better represent the complex network of relationships among multi-intelligent nodes and provide a reference for intelligent decision-making of complex systems.
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