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Naslov:Last-mile delivery optimization considering the demand of market distribution methods: a case studies using Adaptive Large Neighborhood Search algorithm
Avtorji:ID Huang, Q. L. (Avtor)
ID Wang, W. J. (Avtor)
ID Liang, X. J. (Avtor)
ID Xu, L. (Avtor)
ID Niu, X. Y. (Avtor)
ID Yang, X. Y. (Avtor)
Datoteke:.pdf APEM17-3_350-366.pdf (1,81 MB)
MD5: 5293BA23A891D66CDC2F12514AE6D622
 
URL https://apem-journal.org/Archives/2022/APEM17-3_350-366.pdf
 
Jezik:Angleški jezik
Vrsta gradiva:Članek v reviji
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FS - Fakulteta za strojništvo
Opis:Based on the current situation and problems of transportation "last mile" transportation distribution, this paper establishes a path optimization model based on user distribution methods from the perspective of market preference for transportation distribution methods, designs an Adaptive Large Neighborhood Search (ALNS) algorithm, and builds a user portrait based on the solution algorithm and the construction method. Based on the solution algorithm and the user portrait construction method, the solution scenario is established, and the distribution route and transportation distribution method are planned based on five real location data. Through the analysis of the solution scenarios, it can be obtained that after the optimization of the model, the transportation distribution cost of enterprises can be reduced, and the satisfaction of the transportation distribution service quality can be improved. The higher the complaint cost, the lower the total transportation and distribution cost, and the higher the satisfaction rate; the higher the time window penalty cost, the higher the total distribution cost, and the lower the satisfaction rate. Through several model comparisons, it is found that the optimized model has obvious advantages in transportation cost and good performance in transportation service satisfaction. To further strengthen the promotion and application of the distribution path optimization model, countermeasures are proposed in three aspects: establishing a unified end transportation information service platform, increasing the investment in end transportation path optimization, and strengthening the formulation of supporting policies to realize the optimization of end distribution services.
Ključne besede:transportation, last mile, Adaptive Large Neighborhood Search (ALNS), market demand, logistics, distribution, optimization, heuristic algorithms
Status publikacije:Objavljeno
Verzija publikacije:Objavljena publikacija
Poslano v recenzijo:19.02.2022
Datum sprejetja članka:31.08.2022
Datum objave:30.09.2022
Založnik:Chair of Production Engineering (CPE), University of Maribor Faculty of Mechanical Engineering
Leto izida:2022
Št. strani:str. 350-366
Številčenje:Vol. 17, no. 3
PID:20.500.12556/DKUM-97165 Novo okno
UDK:656:004
COBISS.SI-ID:269178115 Novo okno
DOI:10.14743/apem2022.3.441 Novo okno
ISSN pri članku:1854-6250
Avtorske pravice: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.
Datum objave v DKUM:20.02.2026
Število ogledov:165
Število prenosov:2
Metapodatki:XML DC-XML DC-RDF
Področja:Ostalo
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Gradivo je del revije

Naslov:Advances in production engineering & management
Skrajšan naslov:Adv produc engineer manag
Založnik:Fakulteta za strojništvo, Inštitut za proizvodno strojništvo
ISSN:1854-6250
COBISS.SI-ID:229859072 Novo okno

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:transport, prevoz, povpraševanje, logistika, distribucija, optimizacija, hevristični algoritem


Zbirka

To gradivo je del naslednjih zbirk del:
  1. Advances in production engineering & management

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