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Title:Designing efficient algorithms for logistics management : optimizing timeconstrained vehicle routing
Authors:ID Bala, Karlo (Author)
ID Fale, Martin (Author)
ID Gvozdenović, Nebojša (Author)
ID Kramberger, Tomaž (Author)
ID Brcanov, Dejan (Author)
Files:.pdf Bala_2025_Designing_efficient_algorithms.pdf (407,50 KB)
MD5: E466576B3CB6BA16EC00530254BC070C
 
URL https://doi.org/10.5937/StraMan2400018B
 
Language:English
Work type:Scientific work
Typology:1.01 - Original Scientific Article
Organization:FL - Faculty of Logistic
Abstract:Background: City logistics is a critical component of urban economic development, as it optimizes supply chains, enhances customer satisfaction through reliable deliveries, and minimizes environmental impacts in densely populated areas. This field addresses various challenges, including traffic congestion, environmental concerns, noise pollution, and the crucial need for timely deliveries. Routing and scheduling are central to logistics operations, with modern software integrating time windows to meet precise scheduling demands driven by detailed customer requirements and operational efficiencies. Furthermore, advanced vehicle routing models now effectively simulate real-world factors such as traffic congestion, stochastic travel times, and dynamic product demands. Purpose: This paper aims to develop an algorithm that addresses the routing decisions. Our approach extends to the time dimension, considering travel times and customer service times within predefined time windows. Study design/methodology/approach: The proposed algorithm is structured to execute in iterative phases, aiming to optimize key logistical objectives. In order to generate competitive solutions, we seek to minimize the number of vehicles utilized and overall travel costs. The evaluation of solution space was conducted via Simulated Annealing. Findings/conclusions: The performance of the proposed algorithm, evaluated using the Gehring and Homberger benchmark instances for 200 customers, demonstrates its effectiveness. The algorithm successfully meets the target number of vehicles required, and the associated travel costs are on average within 1% of the best solutions reported in the relevant literature. Limitations/future research: Given the ongoing need for timely solutions from decision-makers, future research endeavors will focus on enhancing the computational efficiency of the algorithm. Additionally, incorporating more time-related features, such as stochastic travel times, could further improve the algorithm's real-time applicability.
Keywords:city logistics, vehicle routing, simulated annealing, time windows, scheduling
Publication status:Published
Publication version:Version of Record
Submitted for review:05.07.2024
Article acceptance date:15.01.2025
Publication date:11.02.2025
Publisher:University of Novi Sad, Faculty of Economics
Year of publishing:2025
Number of pages:11 str.
PID:20.500.12556/DKUM-92297 New window
UDC:005:656.1
ISSN on article:2334-6191
COBISS.SI-ID:227110403 New window
DOI:10.5937/StraMan2400018B New window
Note:Ključne besede v slovenščini: logistika v mestih, načrtovanje voznih poti, simulirano ohlajanje, časovni okviri, razporejanje nalog (prevedel bibliotekar)
Publication date in DKUM:27.03.2025
Views:176
Downloads:7
Metadata:XML DC-XML DC-RDF
Categories:Misc.
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Record is a part of a journal

Title:Strategic management
Shortened title:Strateg. manag.
Publisher:University of Novi Sad, Faculty of Economics
ISSN:2334-6191
COBISS.SI-ID:512586301 New window

Document is financed by a project

Funder:Ministry of Education, Science and Technological Development of the Republic of Serbia
Project number:174018
Name:Algebraic, logical and combinatorial methods with applications in theoretical computing

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.
Licensing start date:11.02.2025

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