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Prediction of FTL Transport Cost Based on Historical Data and Multiple Linear Regression Model

  • Warsaw Stock Exchange
  • Silesian University of Technology
  • Institute of Innovative Technologies EMAG

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

There are many components involved in calculating transport costs for specific destinations in a transportation company. In this research the problem of price prediction in FTL transport, based on real data and linear regression mode is investigated. Four different cases and corresponding algorithms, depending on conditions imposed to locations of loading/unloading point, as well as on the detection of more expensive regions to serve are proposed. Statistical analysis of models trained on real data indicate very high accuracy of expected price predictions.

Original languageEnglish
Title of host publicationModelling and Simulation 2023 - European Simulation and Modelling Conference 2023, ESM 2023
EditorsRob Vingerhoeds, Pierre de Saqui-Sannes
PublisherEUROSIS
Pages213-216
Number of pages4
ISBN (Electronic)9789492859280
Publication statusPublished - 2023
Event37th Annual European Simulation and Modelling Conference, ESM 2023 - Toulouse, France
Duration: 24 Oct 202326 Oct 2023

Publication series

NameModelling and Simulation 2023 - European Simulation and Modelling Conference 2023, ESM 2023

Conference

Conference37th Annual European Simulation and Modelling Conference, ESM 2023
Country/TerritoryFrance
CityToulouse
Period24/10/2326/10/23

Keywords

  • Automated pricing module
  • Linear Regression model
  • Logistics
  • Machine learning-supported simulation
  • Real-data example

ASJC Scopus subject areas

  • Modeling and Simulation

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