• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

Computer Engineering & Science ›› 2022, Vol. 44 ›› Issue (12): 2255-2265.

• Artificial Intelligence and Data Mining • Previous Articles     Next Articles

A multi-objective fireworks algorithm with two-archive coevolution for low-carbon cold chain distribution optimization of vaccines

SHEN Xiao-ning1,2,3,YOU Xuan1,CHEN Qing-zhou1,PAN Hong-li1,HUANG Yao1   

  1. (1.School of Automation,Nanjing University of Information Science and Technology,Nanjing 210044;
    2.Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology,Nanjing 210044;
    3.Jiangsu Key Laboratory of Big Data Analysis Technology,Nanjing 210044,China)
  • Received:2021-05-12 Revised:2021-06-28 Accepted:2022-12-25 Online:2022-12-25 Published:2023-01-05

Abstract: 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.

Key words: low-carbon, vaccine distribution, multi-objective optimization, fireworks algorithm, constraint handling, coevolution