Vaccine Delivery Route Optimization Based on Hybrid Equilibrium Optimization Algorithm
Aiming at the optimization problem of vaccine distribution route,a vehicle routing optimization model aiming at minimizing vaccine distribution cost is proposed in this study,considering the fixed,transportation,refrigeration,carbon emission,and penalty costs.To solve the model,the Simulated Annealing(SA)algorithm is introduced into the Equilibrium Optimizer(EO)algorithm to improve the shortage of the EO algorithm,which is easy to fall into the local optimal.The variable parameters are added to improve the ability of the algorithm to balance the global search and local optimization,and a hybrid EO algorithm that can stably obtain high quality solutions is obtained.By conducting 20 experiments on two examples with different scales,the hybrid EO and parallel balance optimization algorithms,the knowledge based,hybrid variable neighborhood search algorithm,improved hybrid particle swarm optimization,ant colony algorithm,and the EO algorithm are compared.The results demonstrate that the standard deviation of the minimum and minimum distribution costs obtained by the hybrid EO algorithm is smaller than that of the other five algorithms in the case of small or large-scale calculation.For instance,the minimum distribution cost obtained in the case of small-scale calculation is 73.5%,53.9%,69.1%,64.1%,and 33.4%of the other five algorithms,respectively.
国家科技期刊平台
NSTL
万方数据
