Aiming at the vehicle routing problem of the mixed fleet of electric vehicles and fuel vehicles considering both pick-up and delivery and time of use electricity tariffs,a vehicle routing optimization model for fresh food distribution has been constructed with the objective of minimizing the sum of the fixed vehicle cost,driving cost,refrigeration cost,cargo damage cost,time window cost,carbon emission cost and charging cost,and a hybrid genetic simulated annealing algorithm integrating neighborhood search is designed for solution.The results show that compared with the separation of pickup and delivery,the simultaneous pickup and delivery mode can significantly improve the distribution efficiency and vehicle loading rate;properly increasing the battery capacity of electric vehicles through technical upgrading can weaken the dependence of vehicle routing schemes on charging facilities and effectively reduce distribution costs;by comparing with the running results of the genetic algorithm and hybrid genetic algorism-variable neighborhood search algorithm,the effectiveness of the algorithm is verified.References are provided for cold chain logistics enterprises to achieve energy conservation and emission reduction,cost reduction and efficiency increase in the distribution link.
hybrid fleetgenetic simulated annealing hybrid algorithmcold chain logisticselectric vehicle distributionpick-up and deliverytime of use electricity tariffs
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