Digital-twin-driven production logistics synchronization system for vehicle routing problems with pick-up and delivery in industrial park

ABSTRACT

With the continuous pressures on customized requirements demands, large-scale multiple-stage production systems in industrial parks are suffering from the complex dynamic impact of uncertainties. These uncertainties are caused by the randomness of customer orders, dynamics of production demand, the uncertainty of production resources, etc. It brings enormous challenges to system operation and decision-making for the Production Logistics (PL) system, which includes how to acquire the full-scale, accurate and real-time execution status of the PL system, and how to make a systematic and adaptability decision by synchronizing every stage in the system under the uncertainties. Taking the PL system of an industrial park as the research object, this paper analyses the problems and challenges in the operation mode of the transportation stage, the perception of dynamics, and the synchronization management and control between the related stages in the dynamic environment. Then the mode of Vehicle Routing Problems with Pick-up and Delivery (VRPDP) is improved and a digital twin-driven decision-making information architecture is proposed, meanwhile, a real-time dynamic synchronization control mechanism is developed to synchronizing the PL system through the transportation stage. Finally, a case study is proposed to verify the feasibility and validity of the proposed method under dynamic disturbance.

KEYWORDS:

• Digital twin
• industrial park
• vehicle routing problems with pick-up and delivery (VRPBD)
• synchronization
• optimization

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work is supported by National Natural Science Foundation of China [51875251], Guangdong Special Support Talent Program – Innovation and Entrepreneurship Leading Team [2019BT02S593], 2018 Guangzhou Leading Innovation Team Program (China)[201909010006], Natural Science Foundation of Guangdong (China) [2016A030311041], Blue Fire Project (Huizhou) Industry-University-Research Joint Innovation Fund of Ministry of Education (China) [CXZJHZ201722], Fundamental Research Funds for the Central Universities (China) [11618401], and the Science and Technology Development Fund (FDCT), Macau SAR [file No. 0017/2019/A1].