基于遗传禁忌搜索的单车场多目标区域调度优化

区域调度是公交营运调度的发展方向,但区域调度相对于传统的线路调度,其影响因素多,模型构建难度大,求解也较为复杂。以单车场区域调度为对象,选择公交车辆空驶时间、等待时间、跨线次数以及运力规模最小等主要目标,构建了多目标区域调度优化模型。考虑到多目标函数优化问题的复杂性,将禁忌搜索融入遗传算子,设计遗传禁忌搜索求解算法,最后将已建模型和设计算法运用到算例中。计算结果表明,遗传禁忌算法较一般遗传算法更能高效地解决公交车辆的单车场多目标区域调度问题。

Optimization of the multi-objective regional dispatching model for single-depot based on the genetic-tabu search algorithm

Regional dispatching is the development direction of bus operation dispatching. The regional dispatching has many influential factors; in addition,the model is difficult to build and to solve, compared with the traditional route dispatching. The multi-objective regional dispatching model is established. Several indicators about the deadhead time, the waiting time, the times of crossing the route for dispatching and the scale of transport capacity, have been involved in the model comprehensively. Considered the complexity of the problem in multi-objective function optimization, the designed algorithm has improved the operator＇s ability to climb a mountain by combing Tabu Search with genetic operators.Final- ly, an illustrative example analysis was given and proved the availability of the model and the genetic-tabu search algorithm.The calculation results show that genetic tabu algorithm can solve the problem of the multi-objective regional dispatching model for single-depot more efficient in the general genetic algorithm than in the genetic-tabu search algorithm.