多线路准快速公交调度优化及混合遗传禁忌算法仿真

针对多线路准快速公交社会效益及企业运营效益最大化的多目标调度问题建立了优化模型。根据问题的特点设计了组合优化调度问题的混合遗传—禁忌算法，结合深圳市龙岗区公交调查数据对该模型进行了验证，计算结果及分析表明该算法比遗传算法及禁忌算法在求解此类问题时有更高的效率。

Simulation of hybrid genetic tabu algorithm for quasi-bus rapid transit scheduling optimization with multi-line

This paper focused on the scheduling problem for Quasi-Bus Rapid Transit with multi-line based on the maximum of the social benefit and enterprise profit. The multi-object math-emtical model of scheduling was established, of which hybrid genetic tabu algorithm was designed for B-asing according to the characteristics of the problem. The model has been validated through surveyed data of the public bus station in Long Gang district of Shenzhen city. The result and analysis show that this algorithm is more efficient than genetic algorithm and tabu search on solving this problem.