Stochastic dynamic vehicle routing problem survey

The present article aims to offer an exhaustive and in-depth investigation of the Stochastic Dynamic Vehicle Routing Problem, which remains a significant challenge in the field of transportation logistics. To achievethis objective, we will undertake a meticulous analysis of the latest cutting-edge techniques and methodologies deployed to tackle this complex optimization problem. Furthermore, we will delve into the intricate and multifaceted stochastic and dynamic constraints that pose formidable obstacles to effective route planning and optimization. Through this survey paper, we seek to provide a comprehensive understanding of the current state-of-the-art approaches and highlight the potential avenues for future research in this critical area of transportation logistics. In addition, we will also analyze the application of advanced reinforcement learning methods and Markov decision processes to solve the problem of stochastic dynamic vehicle routing.

Authors

Publication Details

Journal
Suleyman Demirel University Bulletin Natural and Technical Sciences
Published
2024-10-15
DOI
https://doi.org/10.47344/sdubnts.v62i1.959
Citations
2
Primary Topic
Vehicle Routing Optimization Methods
Type
article
Field-Weighted Citation Impact
0.70
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article

Stochastic dynamic vehicle routing problem survey

Yernar Akhmetbek
2 citations
Suleyman Demirel University Bulletin Natural and Technical Sciences
Vehicle Routing Optimization Methods
0.70
article

Stochastic dynamic vehicle routing problem survey

Yernar Akhmetbek
article en
2 citations

Abstract

The present article aims to offer an exhaustive and in-depth investigation of the Stochastic Dynamic Vehicle Routing Problem, which remains a significant challenge in the field of transportation logistics. To achievethis objective, we will undertake a meticulous analysis of the latest cutting-edge techniques and methodologies deployed to tackle this complex optimization problem. Furthermore, we will delve into the intricate and multifaceted stochastic and dynamic constraints that pose formidable obstacles to effective route planning and optimization. Through this survey paper, we seek to provide a comprehensive understanding of the current state-of-the-art approaches and highlight the potential avenues for future research in this critical area of transportation logistics. In addition, we will also analyze the application of advanced reinforcement learning methods and Markov decision processes to solve the problem of stochastic dynamic vehicle routing.

Suleyman Demirel University Bulletin Natural and Technical SciencesVol. 62(1)
Openalex Percentile: Top 23%
Vehicle Routing Optimization Methods
0.70
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Stochastic dynamic vehicle routing problem survey — Yernar Akhmetbek · Suleyman Demirel University Bulletin Natural and Technical Sciences (2024) | TGRS Research Map | TGRS