采用双档案协同进化离散多目标烟花算法的低碳疫苗冷链优化配送

建立低碳疫苗冷链配送问题的约束多目标优化模型，在满足可用车数量、车辆容量约束和时间窗约束的条件下，考虑最小化碳排放的企业运输成本和客户不满意度。提出一种双档案协同进化的离散多目标烟花算法，采用消除车辆数量和容量约束的解码方式，设计了部分映射爆炸算子，设置可行解档案和不可行解档案协同进化，并对不可行解档案实施可行性搜索。实验结果表明，与已有算法相比，所提算法在低碳疫苗冷链配送问题上能高效地搜索到一组收敛精度和分布性能更优的Pareto非支配解。

A multi-objective fireworks algorithm withtwo-archive coevolution for low-carbon coldchain distribution optimization of vaccines

A constrained multi-objective optimization model for the low-carbon-cold chain distribution of vaccines is established to minimize the corporate transportation costs including the cost of carbon emissions and customer dissatisfaction, satisfying the constraints of the number of available vehicles, vehicle capacity and time window. A discrete two-archive-based multi-objective fireworks algorithm is proposed. The decoding method that can meet the constraints of the number of available vehicles and vehicle capacity is adopted. The partial mapping explosion operator is designed. Feasible solution archive and infeasible solution archive are set for coevolution. Feasibility search is performed on the infeasible solution archive. Experimental results show that, compared with the existing algorithms, the proposed algorithm can effectively obtain a group of Pareto non-dominated solutions with better convergence and distribution.