Logistics Network with Cutting-Edge Algorithm System
Technology is shaping the future of logistics. The logistics sector embraced technology during the pandemic time to avoid disruptions. Companies had a tough time in estimating demands, allocating capacities transporting products, stressing over the need for rapid adoption of technological solutions. The benefits of technology are manifold from visibility to minimizing costs and errors to improving operational efficiency turn around times and speed.
Technology solutions such as AI, big data, IoT, automation, and robotics are transforming the logistics sector. AI is being used to predict and plan logistics with a focus on capacity planning, network optimization, and last mile delivery optimization. Deploying AI and automation/robotics in freight(autonomous trucks), along with intelligent warehousing (machine vision, automated guided vehicles) can create a fully automated supply chain. Big data and analytics are being used in realtime tracking and tracing. Blockchain has also been a strategic focus for the industry, in considering data and identity security aspects related to logistics data.
Introducing Transport Decompression Algorithm System in the industry will turn the scale upward by more than 10 percent
According to a report by the World Economic Forum, titled 'The digital transformation of logistics: Threat and opportunity', the total opportunity for digital transformation in the logistics sector is more than $4 trillion (2025). Investors have been investing into last mile delivery solutions and platforms for information solutions and logistics services. The total global sectoral funding in 2021 was over $20 billion. Technology is an important enabler in providing end to end services to its customers. Logistics companies are nowadays working on the technology like TMS for tracing and tracking, ERP SAP for accounting and invoicing, and other pilot applications contributing to efficient functioning of the supply chain management. Logistics Industries are constantly seeking new ways at improving operational efficiencies in order to provide cost effective transportation solutions to its customers.
Introducing Transport Decompression Algorithm System in the industry will turn the scale upward by more than 10 percent. AI-powered algorithms tend to have a higher accuracy rate in comparison to the traditional methods of forecasting, as they take all factors into consideration. Logistics companies can achieve the realtime information by using such technologies. TES is short for Technology, Engineering, System & Solution and refers to the core technologies. This cutting-edge technique & innovation will be successfully implemented in India in a long run. This algorithm system will provide the most efficient transport network and operational information by analyzing big data of transport vehicles(large consignments) going to and from logistics centers to its customers. This Big Data analysis will provide the most efficient transportation network and operational information. Big data is a quantum leap in the field of logistics. A big data platform can go through tons of data resources, identify, and analyze relevant information. Accurate data will help us in performing effectively. By using this technology we can lower down the marginal errors and identify future opportunities quicker than the companies that rely on manual computation systems.
Big data allows for objective data analysis that considers parameters such as sourcing, supply chain efficiency, end-to-end management, and other functions. Since it does away with dependency on human intuition and judgment, it leads to higher efficiency. This algorithm system is applied to various logistics businesses that require transportation capabilities, such as parcel delivery and contract logistics. Unlike the existing simple dispatch method, the transport decompression algorithm system comprehensively analyses various information related to transport vehicles. It provides an optimized logistics network solution based on Big Data related to transport vehicles, such as origin, destination, vehicle type, and route.
Such network optimization not only minimizes the proportion of transport vehicles moving without cargo, but also reduces carbon emissions by shortening the total travel distance. In addition, it is possible to predict the required number of vehicles in advance based on big data, thereby maximizing operational efficiency. While technology adoption has many benefits, according to a McKinsey report, only 21 percent of logistics companies in India have implemented digitalization in products and services and only two percent have implemented it in the supply sector.