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Model for selective vehicle problem considering mixed fleet with capacitated electric vehicles.
Jiacheng Li1, Masato Noto1, Yang Zhang2
1Department of Applied Systems and Mathematics, Kanagawa University, Yokohama, Japan.
Scientific Reports
|July 2, 2025
Summary
Optimizing last-mile delivery with electric vehicles (EVs) is crucial. A new algorithm improves delivery completion and reduces energy use in mixed fleets, showing 80% EV adoption maximizes benefits.
Area of Science:
- Operations Research
- Logistics Management
- Sustainable Transportation
Background:
- The increasing adoption of electric vehicles (EVs) necessitates new strategies for last-mile delivery operations.
- Logistics providers face challenges in balancing energy consumption, delivery completion rates, and emissions with mixed fleets.
- Addressing self-loading and energy constraints of diverse vehicle types is critical for efficient delivery.
Purpose of the Study:
- To develop a multi-objective optimization model for last-mile delivery using mixed fleets of conventional and electric vehicles.
- To maximize service completion, minimize energy consumption, and reduce emissions.
- To propose and validate an advanced optimization algorithm for logistics fleet management.
Main Methods:
- Formulation of a multi-objective optimization model considering vehicle constraints and delivery objectives.
- Development of an adaptive large neighborhood search (ALNS) algorithm, enhanced with simulated annealing and local search principles.
- Comparative analysis of the proposed ALNS algorithm against traditional optimization methods using test instances.
Main Results:
- The proposed ALNS algorithm demonstrates superior performance and computational efficiency compared to existing methods.
- The algorithm achieved solution improvements ranging from 2% to 15% over traditional algorithms.
- Analysis indicates that achieving the full benefits of energy conservation and emission reduction requires an 80% proportion of electric vehicles in the fleet.
Conclusions:
- The developed optimization model and ALNS algorithm effectively address the complexities of last-mile delivery with mixed fleets.
- Fleet managers can leverage these findings for strategic decision-making regarding EV integration and operational efficiency.
- Achieving significant environmental and economic advantages in logistics relies on a substantial commitment to electric vehicle adoption.
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