Short Review in Green Vehicle Routing Problem with Pick-up and Delivery and Time Windows Using Metaheuristics

Integrating sustainability is a crucial process that every organization must incorporate into its supply chain. Transportation is one of the primary contributors to carbon emissions, accounting for approximately 24% of global CO 2 emissions. Notably, road transport is responsible for nearly 75% of these total emissions worldwide, according to recent studies conducted by the International Energy Agency (IEA) in 2021. This paper explores the Green Vehicle Routing Problem (GVRP), which represents an extension of the classical Vehicle Routing Problem (VRP). GVRP integrates environmental considerations by focusing on reducing the carbon footprint. Within this framework, we focus on the Green Vehicle Routing Problem Pickup and Delivery with Time Windows (GVRPPDTW) variant, which introduces additional complexity by requiring vehicles to serve customers with specific pickup and delivery requests within predefined time windows. This variant reflects realistic constraints in the logistics field, such as schedule synchronization and the balance between efficiency and customer satisfaction. This study presents a short comprehensive review conducted over the period 2017-2024, identifying and analyzing research conducted in the context of this variant and analyzing the efficiency of using metaheuristic algorithms in solving this optimization problem. We will discuss existing research gaps and propose future directions for further advancements in the field. This analysis aims to provide a comprehensive understanding of GVRPPDTW, offering valuable insights for researchers and practitioners seeking to address its challenges.

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Publication Details

Journal
The Open Transportation Journal
Published
2025-02-20
DOI
https://doi.org/10.2174/0126671212375850250212065147
Citations
1
Primary Topic
Vehicle Routing Optimization Methods
Type
article
Field-Weighted Citation Impact
1.24
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article

Short Review in Green Vehicle Routing Problem with Pick-up and Delivery and Time Windows Using Metaheuristics

Nadia Berrahmania, Elhachmi Hammou, Lekbira El Fadi
1 citations
The Open Transportation Journal
Vehicle Routing Optimization Methods
1.24
article

Short Review in Green Vehicle Routing Problem with Pick-up and Delivery and Time Windows Using Metaheuristics

Nadia Berrahmania, Elhachmi Hammou, Lekbira El Fadi
article en
1 citations

Abstract

Integrating sustainability is a crucial process that every organization must incorporate into its supply chain. Transportation is one of the primary contributors to carbon emissions, accounting for approximately 24% of global CO 2 emissions. Notably, road transport is responsible for nearly 75% of these total emissions worldwide, according to recent studies conducted by the International Energy Agency (IEA) in 2021. This paper explores the Green Vehicle Routing Problem (GVRP), which represents an extension of the classical Vehicle Routing Problem (VRP). GVRP integrates environmental considerations by focusing on reducing the carbon footprint. Within this framework, we focus on the Green Vehicle Routing Problem Pickup and Delivery with Time Windows (GVRPPDTW) variant, which introduces additional complexity by requiring vehicles to serve customers with specific pickup and delivery requests within predefined time windows. This variant reflects realistic constraints in the logistics field, such as schedule synchronization and the balance between efficiency and customer satisfaction. This study presents a short comprehensive review conducted over the period 2017-2024, identifying and analyzing research conducted in the context of this variant and analyzing the efficiency of using metaheuristic algorithms in solving this optimization problem. We will discuss existing research gaps and propose future directions for further advancements in the field. This analysis aims to provide a comprehensive understanding of GVRPPDTW, offering valuable insights for researchers and practitioners seeking to address its challenges.

The Open Transportation JournalVol. 19(1)
Mohammed V University (MA)
Openalex Percentile: Top 22%
Vehicle Routing Optimization Methods
1.24
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