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A Time-Dependent Vehicle Routing Problem for Instant Delivery Based on Memetic Algorithm.
Shuxian Cui1, Qian Sun1, Qian Zhang1
1School of E-business and Logistics, Beijing Technology and Business University, Beijing 100048, China.
This study introduces a new model for instant delivery route planning, balancing cost and customer satisfaction in urban logistics. A novel algorithm optimizes delivery routes considering traffic and customer time windows.
Area of Science:
- Operations Research
- Logistics and Supply Chain Management
- Transportation Science
Background:
- Instant delivery is crucial for same-city online-to-offline (O2O) services and urban short-distance logistics.
- Effective route planning must balance delivery costs with customer satisfaction.
- Dynamic traffic conditions significantly impact delivery efficiency and scheduling.
Purpose of the Study:
- To develop a vehicle routing problem (VRP) model for instant delivery.
- To incorporate two distinct customer time windows into the VRP model.
- To account for time-dependent road networks in route optimization.
Main Methods:
- Proposed a novel vehicle routing problem model tailored for instant delivery scenarios.
- Integrated two types of customer time windows to enhance delivery flexibility.
- Developed a memetic algorithm, combining genetic algorithms and variable neighborhood search, for efficient problem-solving.
Main Results:
- The proposed model and algorithm effectively addressed the complexities of instant delivery routing.
- Comparative analysis across different time periods validated the algorithm's performance.
- Sensitivity analysis confirmed the model's robustness regarding customer time windows.
Conclusions:
- The developed VRP model and memetic algorithm provide an effective solution for optimizing instant delivery.
- The approach successfully balances cost, customer satisfaction, and dynamic traffic conditions.
- This research offers a valuable tool for improving urban logistics and O2O service efficiency.

