基于混合蚁群算法的重调度低碳城市配送

Low carbon of rescheduling in urban distribution based on hybrid ant colony algorithm

为减少城市配送车辆产生大量碳排放的问题,提出在时变网络下,以碳排放量、里程和时间为优化目标,建立低碳动态重调度配送模型。采用模拟退火与蚁群算法相结合,提高算法跳出局部最优的能力;通过自适应精英个体繁殖策略,提高种群优良基因个数;引入包含碳排放的多因子算子,增强信息素更新的方向性。模拟算例结果表明,该模型能够有效减少配送过程中的碳排放量,验证了混合算法的高效性。

To reduce carbon emissions produced by vehicles in city distribution,it was proposed to establish a low-carbon dynamic rescheduling distribution model under the condition of time-varying network with the optimization objectives of carbon emission,mileage and time.A combination of simulated annealing and ant colony algorithm was used to improve the ability of the algorithm to jump out of the local optimization.The strategy of adaptive elite individual reproduction was used to increase the number of excellent genes in the population.A multi-factor operator including carbon emission was introduced to enhance the directionality of information element update.The simulation example shows that the model can reduce the carbon emissions effectively in the distribution process,and the effectiveness of the algorithm is also verified.