A Scalable Microservice Framework for Multi-Modal Logistics Route Optimization
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Abstract
In this paper, I am going to present a scalable logistics route planning microservice software that could be implemented to optimize the supply chain and ensure that it is more efficient, flexible, and resilient. The pressure to identify efficient and sustainable logistic operations in fast, cost-effective and environmentally-safe freight transportation, and the need of faster, agile and multi-modal route planning, implies it. The classic centralised route planning lacks the ability to address the dynamical, large, as well as multi-modal transportation system. We decentralise also the logistics (microservices) such as the data collection, prediction, assigning routes and assigning vehicles, monitoring the traffic conditions, cost and analytics. It offers real time connection to any kind of transport network (road, railway, air and sea) that is scalable and resilient to faults. Both the data sources and the intelligent decision-making models utilise data in real-time; the data sources gather and capture real-time data to optimise dynamically and identify the optimal alternative path to identify the cost-efficient paths. The systems are also capable of interconnecting with other systems like the warehouse management systems, fleet management systems and the enterprise resource planning systems. The needed scale and a range of logistics use-cases are provided with the help of containers and API-based communication and distributed model. In the paper, the benefits of the innovations in route planning, computational issues and sustainable logistics based on microservices are outlined. Plainly, it is by the framework that the logistics companies will have a treasure trove and scalable solution to the logistic and supply chain giving the revitalization to the efficiency and precision as well as decision making capacities of the multi-mode transport.
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