蜂群激发抑制算法及其在交通信号配时中的应用

Bee Colony Activating-Inhibition Algorithm and Its Application in Traffic Signal Timing

现实生活中存在各种各样的动态分配问题,群智能劳动分工由于模拟的是生物群体之间的协作分工,所以在解决这类动态分配问题有着天然的优势。目前对群智能劳动分工的研究主要集中在蚁群的刺激响应原理,而忽略了蜂群的激发抑制原理。与刺激响应原理的个体环境交互方式不同,激发抑制原理采用的是个体个体交互方式。针对蜂群劳动分工现象,提出一种激发抑制劳动分工模型(AILD)。为了验证AILD模型的有效性,选取了一个典型的时间分配问题——交通信号配时,设计了相应的激发抑制劳动分工信号配时算法AILD-ST。采用AILD-ST算法对实际案例进行了交通信号配时求解,并与Webster算法、蚁群算法和蜂群算法进行了对比,通过对比实验和分析讨论,结果显示出本文算法的有效性。

There are various dynamic allocation problems in real life. However, the swarm intelligence division of labor has a natural advantage in solving such dynamic allocation problems because it simulates the division of labor between biological groups.At present, most studies on division of labor with swarm intelligence focus on the stimulation-response principle of ant colonies, while ignores the principle of activating and inhibition of bee colonies. Different from the individual environment interaction mode of the stimulation-response principle, the principle of activating and inhibition adopts interaction mode among individuals. Aiming at the phenomenon of labor division of bee colonies, this paper proposes an activating and inhibition labor division model (AILD). In order to verify the validity of the AILD model, traffic signal timing,a typical time allocation problem,is selected and the corresponding activating and inhibition labor division signal timing algorithm (AILD-ST) based on the evolutionary solution is proposed. This paper uses the real traffic flow data to implement simulation experiment based on AILD-ST algorithm. Compared with Webster algorithm, ant colony algorithm and bee colony algorithm, the results show that the proposed algorithm is of good quality and high calculation efficiency.