20.500.12556/DKUM-96919 Optimization of cold chain multimodal transportation routes considering carbon emissions under hybrid uncertainties 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. cold chain multimodal transportation route optimization hybrid uncertainties niche genetic algorithm dual-pheromone Ant Colony Algorithm robust optimization carbon emissions genetski algoritmi optimizacija emisije ogljika true false true Chair of Production Engineering (CPE), University of Maribor Faculty of Mechanical Engineering Angleški jezik Slovenski jezik https://apem-journal.org/ 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. Članek v reviji 2026-02-02 14:26:48 2026-02-02 14:26:49 2026-02-03 03:14:34 0000-00-00 00:00:00 2024 0 0 str. 315-332 no. 3 Vol. 19 Sept. 2024 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2024-09-27 2024-10-28 2024-10-31 658.5:004.8 266950915 10.14743/apem2024.3.509 1854-6250 APEM19-3_315-332.pdf APEM19-3_315-332.pdf 1 3A245C79AB1AD435FBC848D2845B0E77 31b4709604fb508c2c5947dc8a63c6e81d7552b9b25ea20a1c27fd6d91ce821b 258cb180-003b-11f1-90fc-00155d581219 https://dk.um.si/Dokument.php?lang=slv&id=202984 https://apem-journal.org/Archives/2024/Abstract-APEM19-3_315-332.html 0 329e7bd3-003b-11f1-90fc-00155d581219 https://dk.um.si/Dokument.php?lang=slv&id=202985 Fakulteta za strojništvo Advances in production engineering & management 0 0 0