摘要
针对实际生活中车辆油耗会随着运载量的变化而变化,建立带油耗率车辆路径问题的数学模型,以最小化总成本为目标函数。将运输过程中随运载量变化的油耗率转化成交叉概率,自适应地改变交叉概率,提高算法的全局搜索能力;考虑车辆满载率,设计一种与运载量相关的变异概率,使其逐渐减小并使群体迅速集中,可以抑制早熟。基于以上方法构造的一种自适应遗传算法,实例进行仿真表明,提出的算法在收敛速度和寻优结果两方面略优于自适应遗传算法和遗传算法。
Aiming at the change of fuel consumption with the change of capacity in real life, the item establishes vehicle routing problem （VRP） with fuel consumption rate mathematical model, minimizing the total cost as the objective function. The a- daptive transformation of fuel consumption rate into crossover probability can improve the global search ability. Meanwhile, the mu- tation probability in relation to the carrying capacity can be designed with the load rate into consideration. It can be decreased gradu- ally and concentrated, thus restraining prematurity. The experiments results show that the proposed algorithm is superior to adaptive genetic algorithm （AGA） and genetic algorithm （GA） in the convergence speed and optimal results.
出处
《东莞理工学院学报》
2015年第3期47-54,共8页
Journal of Dongguan University of Technology
