动态混合行为交通网络平衡的遗传算法求解

采用遗传算法对动态交通网络平衡微分博弈模型进行求解,将动态混合行为交通网络平衡模型构造为一个开环信息结构下N个局中人非合作非零和博弈,并考虑了一个单OD对之间有两个平行弧的简单网络和两类局中人——用户平衡(UE)和古诺-纳升(C-N)——在拥挤现象中的相互作用,针对此简单网络阐明了遗传算法求解模型的具体步骤。遗传算法求解不必要求目标函数连续可微,大大提高了模型的适用性。通过算例对所设计的算法进行了验证,在算例中将Wie BW(1993)的研究中部分参数取值作了修改,使其更加合乎交通实际,并将计算结果与Wie B W(1993)采用最小值原理计算结果进行了对比分析,通过对比分析表明,其计算结果更符合交通实际。

Genetic algorithm approach to dynamic mixed behaviortraffic network equilibrium problem

This paper proposes a new simulation algorithm based on genetic algorithm idea for solving the differential game model in discrete time.The model is the dynamic mixed behavior traffic network equilibrium model,which is formulated as a noncooperative N-person nonzero-sum differential game under the open-loop information structure.A simple network is considered where one origin-destination pair is connected by parallel arcs and two types of players-user equilibrium and cournot-nash-interact through the congestion phenomenon.The Genetic algorithm solution program is thoroughly stated.Genetic algorithm does not require continuous and differential of objective function,therefore,the suitability of the model are substantially improved.A numerical example is presented,and the value of some parameters in the work of Byung-Wook Wie(1993) are modified.Compared with the work of Byung-Wook Wie(1993),the computing results in this work accords with the traffic reality more accurately.4 figs,9 refs.