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A multi-objective capacitated vehicle routing problem with heterogeneous fleets for green logistics |
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| รหัสดีโอไอ | |
| Title | A multi-objective capacitated vehicle routing problem with heterogeneous fleets for green logistics |
| Creator | Anantaya Sonklin |
| Contributor | Sun Olapiriyakul, Advisor |
| Publisher | Thammasat University |
| Publication Year | 2568 |
| Keyword | Capacitated vehicle routing problem (CVRP), Multi-objective optimization, Green logistics, Heuristic method |
| Abstract | Efficient transportation planning for perishable goods is increasingly challenging under uncertain demand, dynamic delivery locations, and growing environmental concerns. This study investigates the real-world flower distribution system originating from Pak Khlong Talat, Thailand’s primary wholesale flower market, where transportation operators must determine daily routing and load allocation decisions shortly before departure based on fluctuating provincial orders. To address this complexity, a dynamic multi-objective Capacitated Vehicle Routing Problem (CVRP) with a three-index mathematical formulation is proposed, simultaneously minimizing transportation cost, carbon dioxide (CO₂) emissions, and maximize on-time delivery rate.The model incorporates vehicle capacity constraints, dynamic customer demand, uncertain delivery locations, and load-dependent emission estimation to reflect realistic operational conditions. Single-objective optimization is first solved using Python and the Gurobi optimizer, followed by a multi-objective framework based on the ε-constraint approach. Computational results indicate that the proposed framework can effectively balance economic efficiency, environmental sustainability,and service responsiveness in perishable goods transportation. The study contributes both theoretically to dynamic and green CVRP modeling and practically by providing an adaptive decision-support tool for real-world flower distribution planning. |
