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Title:Optimization of cold chain multimodal transportation routes considering carbon emissions under hybrid uncertainties
Authors:ID Hou, D. N. (Author)
ID Liu, S. C. (Author)
Files:.pdf APEM19-3_315-332.pdf (1,33 MB)
MD5: 3A245C79AB1AD435FBC848D2845B0E77
 
URL https://apem-journal.org/Archives/2024/Abstract-APEM19-3_315-332.html
 
Language:English
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FS - Faculty of Mechanical Engineering
Abstract:As the third largest greenhouse gas emission industry across the globe, the transportation industry dominates a major position in the total carbon emission. Multimodal transportation has incomparable advantages over single-modal transportation, and choosing transportation routes and modes under the background of carbon peaking and carbon neutrality is crucial. The uncertainties of demand and transportation time were described using the maximum regret value and Lyapunov central limit theorem, respectively, and a robust optimization model for cold chain multimodal transportation routes considering hybrid uncertainty of carbon emissions was established. Then, a dual-pheromone ant colony algorithm was designed, and the improved niche genetic algorithm was nested into the ant colony algorithm to solve the model. Results showed that the changes in transportation time and node transfer time lead to the changes in transportation cost and transportation scheme, and the robust optimization of the multimodal transportation route under hybrid uncertainties is affected by the regret value constraint and the fluctuation range of uncertain factors, resulting in the increase in transportation cost and carbon emission cost. Therefore, the decision-makers of cold chain multimodal transportation must predict the influence of uncertain factors, choose the appropriate maximum regret value, and pay attention to the mixed time window constraints of transportation time and node transfer time to reduce costs and improve efficiency.
Keywords:cold chain multimodal transportation, route optimization, hybrid uncertainties, niche genetic algorithm, dual-pheromone Ant Colony Algorithm, robust optimization, carbon emissions
Publication status:Published
Publication version:Version of Record
Submitted for review:27.09.2024
Article acceptance date:28.10.2024
Publication date:31.10.2024
Publisher:Chair of Production Engineering (CPE), University of Maribor Faculty of Mechanical Engineering
Year of publishing:2024
Number of pages:str. 315-332
Numbering:Vol. 19, no. 3
PID:20.500.12556/DKUM-96919 New window
UDC:658.5:004.8
ISSN on article:1854-6250
COBISS.SI-ID:266950915 New window
DOI:10.14743/apem2024.3.509 New window
Copyright:Content from this work may be used under the terms of the Creative Commons Attribution 4.0 International Licence (CC BY 4.0). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
Publication date in DKUM:02.02.2026
Views:186
Downloads:2
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Categories:Misc.
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Record is a part of a journal

Title:Advances in production engineering & management
Shortened title:Adv produc engineer manag
Publisher:Fakulteta za strojništvo, Inštitut za proizvodno strojništvo
ISSN:1854-6250
COBISS.SI-ID:229859072 New window

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

Language:Slovenian
Keywords:genetski algoritmi, optimizacija, emisije ogljika


Collection

This document is a part of these collections:
  1. Advances in production engineering & management

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