Optimization of Cold Chain Logistics Distribution Path Based on Improved Artificial Bee Colony Algorithm
In the process of cold chain distribution,the tem-perature control needs of different goods are different.How to efficiently and low-cost deliver goods with different tempera-ture control needs to customers is one of the important prob-lems that cold chain logistics enterprises need to solve.Con-sidering the demand of residents for goods at different temper-ature levels in practical life,a multi temperature co distribu-tion model is introduced.Under the constraint of vehicle load,a cold chain logistics distribution path model is constructed with the minimum sum of vehicle fixed cost,transportation cost,cargo damage cost,refrigeration cost,and time penalty cost.In response to the problems of slow convergence and premature convergence in traditional artificial bee colony algo-rithms,an elite retention strategy is adopted in the following bee stage to accelerate the convergence speed of the algo-rithm.In the reconnaissance bee stage,genetic algorithm mu-tation operation is combined to avoid the algorithm from falling into local optima too early.An improved artificial bee colony algorithm is designed.Finally,through simulation ex-periments on the example,it was verified that the improved artificial bee colony algorithm can solve for better paths and effectively reduce the cost of cold chain logistics distribution.
万方数据
维普
