A multi-trip vehicle routing problem considering time windows and limited duration under a heterogeneous fleet and parking constraints in cold supply chain logistics

ABSTRACT

Cold supply chain distribution systems ensure the freshness of temperature-sensitive products during transportation. In this study, we investigated a fresh food company’s cold supply chain distribution. Making fresh food available and achieving quality and safety, requires proper planning of vehicle routing, we addressed a routing problem that simultaneously considers time windows, multiple trips per vehicle, a heterogeneous fleet, parking constraints, unloading time at customer position, and limited duration, minimizing related operational costs. We formulate this problem as a mixed-integer programming model. Since this problem is NP-hard, we also propose a genetic algorithm with two adaptive-parameter mechanisms to solve it within a reasonable computational time. Extensive experiments were conducted to assess the performance of different approaches in a real-world application. The results demonstrate that the algorithms are robust and efficient. The proposed algorithms can reduce operational costs by more than 20% compared to the current practical planning approach.

KEYWORDS:

• Cold supply chain
• multi-trip vehicle routing problem
• time window
• limited duration
• adaptive genetic algorithm

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

We thank the Ministry of Science and Technology, Taiwan, ROC , for funding this project under contract no. MOST 110-2221-E-167-027.