Electric vehicle routing models and solution algorithms in logistics distribution: A systematic review

Area of Science:

• Operations Research
• Sustainable Logistics
• Transportation Science

Background:

• Growing adoption of electric vehicles (EVs) in logistics, driven by green initiatives and policy support.
• The Electric Vehicle Routing Problem (EVRP) is a critical area of research for optimizing EV deployment in distribution networks.
• Traditional vehicle routing problems require adaptation to account for EV-specific constraints like battery capacity and charging.

Purpose of the Study:

• To provide a comprehensive review of the latest research on EVRP models and solution algorithms.
• To classify existing EVRP models based on objective functions and constraints.
• To analyze the development trends in EVRP theoretical methods for sustainable logistics.

Main Methods:

• Categorization of EVRP models, including those with load/battery constraints, time windows, charging strategies, hybrid fleets, and charging station location.
• Overview of solution algorithms: exact algorithms, traditional heuristics, meta-heuristics, and hybrid approaches.
• Analysis of commonly used meta-heuristic algorithms for solving EVRP.

Main Results:

• Identification of four main EVRP model types based on objective functions and constraints.
• Summary of various algorithmic approaches for addressing EVRP, with a focus on meta-heuristics.
• Discussion of battery loss considerations in EVRP models.

Conclusions:

• The EVRP is a complex but vital research area for efficient and sustainable logistics operations.
• Further research is needed to refine EVRP models and develop more effective solution algorithms.
• The review identifies key trends and future directions for EVRP theoretical development.