It is becoming critical for companies to Identify and deal with the apertures in the legacy freight management companies using technological innovations. Along with this, there is a need for extensive research and development (R&D) for multimodal transit that includes shipping, railway, air cargo, and trucking sectors as the industry needs standardisation of manual processes and containerization of freight transportation to bring better flexibility and speed.
Author: Aryan Kulkarni at NITISARA, November edition, NITISARA Strategic Insights
Introduction
The evolution of freight management over the years has been marked by significant advancements in technology, changing market dynamics, and an increased focus on sustainability. Furthermore, the advent of technology, the Global Positioning System and convenient software systems has had a burgeoning effect on the entire supply chain industry by raising efficiency, visibility and communications to unprecedented levels. In the case of freight management – booking, scheduling, routing and tracking – time-consuming processes that used to be carried out manually, by hand, can now easily be executed using our mere fingertips, by implementing a few commands on the computer. However, this rapid development of technologies has taken and continues to take a heavy toll on the biosphere. These negative effects are now observed to be aggressively manifesting in the form of drastic changes in weather conditions, and increased frequency of natural disasters. Thus, an all-around effort must be put into integrating eco-friendly factors and sustainable practices into the ever-cooking pot of technological development. Advanced computation and communication, enabled by modern technology, can be directly employed to adopt sustainable practices through route optimization algorithms and, real-time reporting and monitoring of data from the supply chain using the Internet of Things (IoT).
ROUTE OPTIMIZATION IN FREIGHT MANAGEMENT SYSTEMS
According to the Statista Research Department, the transportation sector is the second-largest source of carbon emissions, as 20.2% of all global CO2 emissions originate from here (as of 2023). Moreover, researchers at MIT have further reported that freight transportation makes up 8% of global greenhouse gas emissions, which goes up to 11% if warehouses and ports are included. A considerable chunk of these emissions is bound to come from delivery vehicles travelling longer routes than required, idling in traffic (for trucks and ships) and also through the usage of more than necessary vehicles due to inefficient load and task distribution. The Vehicle Routing Problem (VRP) has grown to be renowned as a classic multi-objective optimization challenge in the field of operation research and logistics, wherein, the objective is to determine the most efficient way to deliver goods or services to a set of locations using a fleet of vehicles while minimizing costs. Depending upon the various real-world scenarios, it has branched into multiple variations, some of which are listed below:
- Capacitated VRP (CVRP): Each vehicle has a limited carrying capacity, and the sum of demands on a route must not exceed this capacity.
- Multiple Depot VRP (MDVRP): There are multiple depots, and vehicles must start and end their routes at the same depot. A similar scenario commonly arises in cases where multiple distribution centres are involved.
- VRP with Pickup and Delivery (VRPPD): In addition to delivering goods, vehicles must also pick up goods at certain locations. In most such real-world cases involving reverse logistics, a separate fleet of vehicles would be used to satisfy deliveries and returns, which would result in net negative returns from deliveries, in turn generating more CO2 emissions (Harrir and Sari-Triqui, 2022).
- Green Vehicle Routing Optimization Problem (G-VRP): Along with the reduction of costs, it strives to optimize routes with an added factor of reduction of environmental impact from fuel emissions of the vehicles.
Solutions to problems like GVRP are not as easy as finding out the shortest routes, because factors such as vehicle type and model, vehicle speeds, loading conditions, etc. become critically important as well (Xiao-Hong Liu, Mi-Yuan Shan, Ren-Long Zhang, Li-Hong Zhang, “Green Vehicle Routing Optimization Based on Carbon Emission and Multi-objective Hybrid Quantum Immune Algorithm”, Mathematical Problems in Engineering, vol. 2018, Article ID 8961505, 9 pages, 2018). Breakthrough advancements in emerging technologies such as machine learning, cloud computing and quantum computing have now enabled ways for much more convenient implementations of different evolutionary algorithms to solve such problems with ever-varying factors. Integration of these algorithms into modern freight management systems is thus considered one of the most effective steps in advancements in freight transportation and logistics, as they directly contribute towards environmental and economic sustainability, improved resource utilization and supply chain resilience, enhanced customer satisfaction and easier compliance with ESG goals.
1. Environmental and Economic Sustainability: Route optimization algorithms not only can identify the most efficient paths, but also help in reducing fuel consumption, leading to lower greenhouse gas emissions and the companies simultaneously save on vehicle maintenance, labour, and other associated expenses.
2. Improved Resource Utilization and Supply Chain Resilience: Capacity is increased through efficient assignment of deliveries to vehicles along with optimization of reverse logistics. Moreover, idle time and idling emissions are minimized, as real-time traffic and weather data and congestion patterns can be taken into account. Dynamically adjusting routes enhances adaptability which helps maintain efficiency under varying circumstances
3. Enhanced Customer Satisfaction: Optimized routes decreasing lead times would positively impact customer satisfaction, directly improving the reliability of the supplier and the loyalty of the customer.
4. Easier Compliance with ESG Goals: By aligning with route optimization strategies that prioritize sustainability, companies are better positioned to comply with increasingly stringent environmental regulations and standards, avoiding potential penalties and reputational damage.
INTERNET OF THINGS FOR MONITORING AND REPORTING
The collection and reporting of data obtained from critical junctures of the supply chain, such as in-transit freight and warehouses, is necessary to ensure that the quality of goods being transported is maintained. This importance is reflected in the report by MarketsAndMarkets, which suggests that the global market for Intelligent Transport Systems (ITS) is projected to grow up to USD 68.0 billion by the year 2026, which is a 10% annually compounded growth rate from its baseline value of USD 42.2 billion in 2021.
This responsibility of data gathering falls upon sensors – devices capable of detecting specific physical inputs. Their usage for monitoring storage conditions is especially exemplified in segments like cold chain, which deal with ESPs (Environmentally Sensitive Products), and require specialized storage technologies. A system such as that designed by Tsang et al. could be used to satisfy this requirement, wherein, a wireless sensor gathers and stores real-time data in a cloud database and fuzzy logic computation is used in the subsequent adjustment of storage conditions. (Tsang Y, Choy K, Wu C, Ho G, Lam H, Koo P. An IoT-based cargo monitoring system for enhancing operational effectiveness under a cold chain environment. International Journal of Engineering Business Management. 2017;9. doi:10.1177/1847979017749063).
The IoT and sensor technologies in tandem with cloud computational resources, and machine learning algorithms, also enable predictive maintenance of freight transport vehicles. In the 2022 report, Gayialis et al. developed a predictive maintenance system for achieving the proactive scheduling of maintenance workshop visits, especially in supply chains involving reverse logistics, where the depreciation of the vehicles is bound to happen at a higher rate. Apart from reductive actions, IoT can also facilitate direct reporting of the emissions from the vehicles involved in the supply chain and of the energy efficiency and carbon footprint of the warehouses/storage facilities in the chain, thus automatically identifying the areas of improvement for the company. Thus, opportunities for highly fruitful synergy with the carbon offsetting market, which Morgan Stanley has forecasted to grow from USD 2 billion in 2022 to USD 100 billion by 2030, are opened up. Integrable APIs by companies like Lune and Cloverly allow the user to tap into and choose from a marketplace of vetted carbon removal projects that could be funded to offset emissions. Bringing the relevant data and tools to take immediate action to address it through interactive dashboards in the freight management systems would be a major step towards industry-wide dissemination of green goals.
CONCLUSION
The report highlights two impactful approaches to incorporating sustainability into the freight management industry – a. Route optimization algorithms, b. Integration of IoT technologies in the critical points along the supply chain. These strategies, though not exhaustive, are holistically effective as they not only spearhead the organization towards positive environmental impact but also toward the amelioration of the company’s economy. The industry still requires long, progressive strides in the course of the development of clean transportation and energy-efficient warehousing solutions. In conclusion, the amalgamation of the technology and sustainability initiatives by corporates, emerging start-up ecosystems, reliable carbon markets, and openness of the legacy freight management industry, will collectively contribute towards a global sustainable growth of this critical sector.