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Preference-agile multi-objective optimization for real-time vehicle dispatching
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DOI：10.1016/j.ejor.2026.04.017.png)
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Abstract
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• An end-to-end Preference-Agile Multi-Objective Optimization (PAMOO) is proposed. • A novel network architecture is tailored with enhanced generalization. • The proposed method facilitates dynamic and interactive preference adjustment in an online setting. • The method marks the first Dynamic Multi-Objective Reinforcement Learning for port operations.
Keywords:
Transportation
Dynamic vehicle routing
Digit port
Multi-objective optimization
Deep reinforcement learning
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