Key Challenges and Common Solutions
Fleet management is a critical function within supply chain operations, especially for companies that prioritize direct control over their logistics to reduce costs and enhance service reliability. Efficiently utilizing the fleet requires addressing several types of problems. In this blog, we explore some of the problems and challenges in fleet management and general approaches to solving them.
Definition
Fleet management involves optimizing the use of vehicles to support a company's operations under various constraints and objectives. Typically, vehicles reside at central locations (a.k.a. hubs, depots, or warehouses). These vehicles are assigned to pick up and deliver goods from various locations and return to the hub at the end of their trip. Sometimes, this includes backhaul optimization, which involves picking up shipments and transporting them back along part or all the routes.
The goal is to efficiently assign vehicles to a set of pickup and delivery tasks while considering factors like cost, time, service, driver and vehicle availability, and more. When done right, it can lead to significant savings compared to some rule-based approaches. For example, a recent project demonstrated a 14% improvement in private fleet utilization, reducing reliance on external carriers, and positively impacting both cost and service. You can find more details about this case study here.
The complexity of fleet management problem arises from various constraints and objectives, including:
Vehicle Capacity: Different vehicles have different capacities.
Time Windows: Each order (a.k.a. goods, items, or loads) usually has a specific time window for pickup and delivery.
Location Hours: Pickup and delivery locations are not usually open 24/7.
Compatibility: Some orders require special equipment. For example, perishable orders require refrigerated trucks.
Fleet Size: Each hub may have a different number of available vehicles. This can be both a constraint or a strategic decision to allocate vehicles to each location to maximize service coverage and utilization. A hub may also have a limited capacity to hold vehicles, so it may not be possible for a vehicle to start its service from one hub and end it in another if the destination hub cannot accommodate it.
Regulatory Compliance: Each driver must adhere to hours-of-service regulations and work limits to ensure safety and legal compliance. For example, in the US, each driver must have at least 10 consecutive off-duty hours after a maximum of 11 hours of driving or maximum of 14 hours of work (driving plus any non-driving work such as loading or unloading), whichever happens first. There are other rules to be considered which can be found in the above link.
Limits on Driver’s Hours: Due to regulatory compliance, contracts, or even objectives (such as maximizing fairness), there may be a limit on the hours a driver can work. For example, driver contracts may specify that a driver should have at least 30 hours of driving time per week, or any work beyond 8 hours per day should be considered overtime.
Balancing Objectives: Minimizing total costs may be the obvious objective. However, some limitations might prioritize other objectives. For example, there may be a constraint to avoid relying on any third-party logistics (3PL) providers or ensuring every order is delivered, regardless of the cost (so, overtime costs or outsourcing become viable options). Or consider a scenario with three drivers and three loads, where one driver can deliver one load, and another can deliver two. Depending on the objectives and constraints, this solution might or might not be acceptable. If the goal is to minimize the number of vehicles used, then this solution is acceptable. However, union contracts or the goal of balanced workloads for each driver may force a different solution, such as assigning one load to each driver, hence, using all 3 drivers.
Fleet management requires solving several optimization problems:
Fleet Sizing and Composition: Deciding the optimal mix and number of vehicles at each hub can be a strategic decision, often informed by historical data analysis across different times and seasons.
Vehicle Routing Problem (VRP): Determining the most efficient routes considering all the constraints is addressed through solving variations of VRP.
Vehicle Assignment and Scheduling: Allocating vehicles to routes based on compatibility, capacity, vehicle availability, and the time windows of each route.
Solution Approaches
Addressing fleet management challenges often involves a combination of techniques, such as Mixed Integer Programming (MIP) and heuristics. Here are two common approaches:
Decomposition Approach
This approach solves each problem separately and integrates the results step-by-step.
Pros:
Specialization: Tailored solutions can address specific challenges in routing or assignment more effectively.
Flexibility: Managing different constraints and objectives within each step allows for a better fit to specific operational needs.
Scalability: Easier to scale operations due to modular nature, without needing to redesign the entire system.
Cons:
Potential for Misalignment: Independent optimization might lead to suboptimal solutions and inefficiencies if the integration is not done properly.
Increased Management Complexity: Managing separate optimization processes can be more complex and may require additional oversight.
Integrated Approach
This approach solves the problems together, considering all variables and constraints simultaneously.
Pros:
Holistic Optimization: By considering all variables and constraints at once, this approach can yield more cohesive and cost-effective outcomes.
Simplified Management: Managing a single comprehensive model can be easier than handling multiple separate ones.
Cons:
Greater Resource Needs: Typically requires more advanced technology, higher computational power, and can be more costly and complex to implement.
Less Flexibility: Adjusting to new constraints or objectives might require significant changes to the model.
These approaches are only two common general strategies; each has its strengths and limitations, and the choice between them depends on the size of the operation and other specific needs and constraints.
Takeaway
For industries where the quality and timing of deliveries are paramount, managing their own fleet can provide significant advantages over relying on third-party logistics. This strategic choice allows businesses to control costs more effectively, optimize operational efficiencies, and maintain high standards of service quality. As market dynamics evolve, advanced fleet management will be increasingly crucial in maintaining competitive advantages in logistics-intensive industries.