Logistics is a broad concept encompassing the entire flow of goods from supply to demand. In the modern supply chain, logistics not only impacts a company’s operational efficiency but also directly influences consumer satisfaction. Therefore, reducing logistics operating costs and improving delivery efficiency have become key concerns for major companies.
With the rise of e-commerce, logistics demand continues to grow. Factors such as transportation costs, labor costs, and fluctuating oil prices are presenting greater challenges for logistics companies. As a key link in the logistics chain, “distribution” is a key area of the logistics chain. Improving efficiency and reducing costs through route optimization is a topic worthy of in-depth discussion.
The original Greek meaning of logistics
The word “logistics” comes from the Greek word λόγος (logos), meaning “calculation, reasoning, logic.” Later, the term was applied to the military, where commanders ensured the precise dispatch of supplies through scientific calculations and strategic planning. In modern business applications, logistics retains this meaning—ensuring the most economical and efficient delivery of goods to their destination through precise data analysis and logical reasoning, a concept also encompassed by operations research.
The relationship between distribution in logistics and its original Greek meaning
Logistics is more than just the delivery of goods; it’s a highly data-driven, scientifically-driven process. Last-mile delivery, as the final link in the logistics chain, directly impacts a company’s operating costs and customer experience. During the delivery process, decision-makers must consider numerous variables, such as:
- Delivery order
- traffic conditions
- Customer time requirements
- Driver working hours and regulatory restrictions
- Fuel consumption and environmental protection requirements
This aligns with the essence of the Greek word λόγος (logos)—making optimal decisions through logic and data calculation. Delivery efficiency doesn’t rely solely on manpower and experience; it requires the support of powerful algorithms. This is where route optimization plays a crucial role.
The key to delivery efficiency: route optimization
Transportation costs account for the largest portion of logistics operating costs, averaging 40% to 60%, according to research. During transportation, the quality of delivery routes directly impacts fuel consumption, labor costs, and delivery timelines.
What is route optimization?
Route Optimization uses mathematical models and algorithms to calculate the shortest or most efficient delivery routes based on real-time information (such as order quantity, delivery location, and traffic conditions) to achieve:
- Reduce driving distance – reduce fuel costs and carbon emissions
- Improve on-time delivery rates – reduce delays caused by traffic jams or incorrect planning
- Improve driver efficiency – reduce driver fatigue and comply with working hours regulations
- Reduce fleet operating costs – reduce vehicle wear and tear and maintenance costs
Common optimization techniques include:
- VRP（Vehicle Routing Problem）：Vehicle routing problem, determining the best delivery route
- TSP（Travelling Salesman Problem）：Traveling salesman problem, determining the shortest route
Through these technologies, companies can significantly reduce distribution costs and improve overall logistics efficiency.
Japan’s 2024 Problem
When it comes to logistics efficiency and operating costs, Japan’s 2024 problem is a topic worth paying attention to. The so-called “2024 problem” refers to the new working hours cap for freight drivers that the Japanese government will officially implement in April 2024, stipulating that freight drivers’ annual working hours cannot exceed 960 hours. This will result in:
- Reduced delivery capacity: Many freight companies will face labor shortages and reduced capacity.
- Rising logistics costs: Due to driver shortages, logistics companies may need to pay higher wages or increase the number of vehicles to cope with demand.
- Delivery delay risk: Consumers and businesses may face longer delivery times
In this environment, route optimization becomes even more critical. Companies that can leverage AI and mathematical models to improve transportation efficiency can maintain stable delivery capabilities within regulatory constraints and even reduce additional operating costs.
How to use route optimization to reduce logistics operation costs?
Companies can use route optimization to reduce logistics operating costs through the following methods:
1.Dynamic Programming Using AI and Data Science
• Use real-time traffic data and weather information to dynamically adjust delivery plans
• Predict order volume based on historical data and plan the optimal delivery route in advance
2. Adopt intelligent order splitting and vehicle dispatching technology
• Automatically assign orders to the most suitable drivers and vehicles through algorithms
• Determine the most efficient delivery method (such as consolidated delivery) based on the size and weight of the shipment
3. Integrate multimodal transport to improve distribution flexibility
• In appropriate scenarios, hybrid transport using rail, trucks, and even drones can reduce costs.
4. Reduce empty vehicle rate and return trip waste
• Arrange new pickup points on return routes to reduce the proportion of empty trucks
5. Introducing SaaS logistics optimization system
• Enterprises can use cloud-based SaaS platforms to automatically calculate the best delivery plan, reducing errors and time costs associated with manual planning.
These methods can not only reduce the operating costs of enterprises, but also improve service quality and make logistics more efficient and environmentally friendly.
In conclusion
Reducing logistics operating costs doesn’t rely solely on reducing manpower or vehicles, but rather on improving overall efficiency through scientific methods. Route optimization, a core technology that impacts delivery efficiency, can help companies reduce haul distances, improve driver productivity, and lower fuel consumption and vehicle maintenance costs, thereby achieving the goal of reducing costs and increasing efficiency.
Especially in the face of external challenges such as the Japan 2024 problem, logistics companies that can effectively leverage AI and optimization algorithms can gain an advantage in market competition and maintain efficient and cost-effective logistics operations.