Multi-objective variable weight combination forecasting model of macro logistics volume based on pccsAMOPSO

  • FAN Dong-fang ,
  • LUO Kai ,
  • JIN Zhi-hong
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  • (Transportation Management College, Dalian Maritime University, Dalian 116026, China)

Received date: 2021-07-16

  Revised date: 2021-10-10

  Online published: 2021-10-10

Abstract

Aiming at the limitations of the existing mediumtolongterm macro logistics volume forecasting models, a multi-objective variable weight combination prediction model (MOVWCP) based on the pccsAMOPSO algorithm was proposed to analyze and predict macro logistics volume. In order to improve the stability of the multi-objective variable weight combination prediction model, the concept of error entropy was proposed, which used as the objective function of the weight programming model together with MAPE. An intelligent heuristic algorithm based on pccsAMOPSO was designed to solve the Pareto front with variable weight in the fitting period, and the variable weight Pareto solution was selected by sensitivity difference. A series of numerical test results verify the superiority of the multiobjective variable weight combination prediction model and its algorithm proposed in this paper.

Cite this article

FAN Dong-fang , LUO Kai , JIN Zhi-hong . Multi-objective variable weight combination forecasting model of macro logistics volume based on pccsAMOPSO[J]. Journal of Dalian Maritime University, 2021 , 47(4) : 19 -29 . DOI: 10.16411/j.cnki.issn1006-7736.2021.04.003

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