Dynamic Fleet Optimization

Dynamic Fleet Optimization is the process of continuously optimizing the management and operation of a fleet of vehicles in real-time. It involves making informed decisions on fleet allocation, scheduling, routing, and other operational aspects based on changing conditions and business objectives.

The first iteration of the tool is available the latest version of RMA 8.1.

It is called Dynamic Fleet Optimization under the Mango Mapping menu item.

Before utilizing the dynamic fleet optimization, it is imperative that the proper setup be done in a number of areas:

• Route Master
• Truck Class
• Products

How to use Dynamic Fleet Optimization

1. To access the Dynamic Fleet Optimization feature in RMA, navigate to Route > Mango Mapping > Dynamic Fleet Optimization.

1. Plotting your initial data on the map is similar to using the Route by Map feature. Begin by selecting the data you want to plot, such as deliveries, dispatch dates, or last delivery points, and then choose the routes you wish to optimize. After making your selections, click Plot to load the data onto the map.

1. Once your data is plotted, you can customize the optimization process using a range of available options. These options fine-tune how the optimization engine balances various factors across each route:

• Sliders for Optimization Focus: Adjust sliders to indicate which areas the optimization engine should prioritize when balancing routes. The higher the slider setting, the more emphasis the engine places on that aspect (note that the exact weight values are still being finalized).
• Include Hourly Wage in Cost/Mile: This option adds the hourly wage of the route’s employee or driver when calculating cost per mile, ensuring that wage costs are factored into route optimization.
• Use All Selected Trucks: By default, the optimization engine may choose to service all stops using fewer trucks if it finds this to be the most efficient solution. Enabling this option forces the engine to use all the trucks you’ve selected, even if fewer trucks could suffice.
• Use Sub Traveling Salesman Problem: This option narrows the search radius for stops, grouping those that are geographically close within the same route. Be aware that enabling this setting causes the optimization process to run until it reaches a timeout, rather than stopping when it finds a seemingly optimal solution.
• Prioritize Furthest Out: This slider adds penalties to stops that are farthest from the starting warehouses, discouraging the optimization algorithm from dropping these stops.
• Low Priority Penalty: This option defines a range (in meters) where penalties are ignored for stops close to the starting warehouse, leading the optimization to deprioritize these stops.
• Use Large Neighborhood Search: Expands the search radius for stops, allowing the optimization engine to create routes that include stops spread farther apart.

1. After plotting your stops and adjusting your optimization settings, click Optimize Fleet to begin selecting which trucks to use for your routes.

1. A new window will appear, displaying a table of available routes and trucks. To ensure a route or truck appears in the list, the following conditions must be met:

• The route must have a valid driver assigned to a truck.
• The truck must belong to a truck class with a defined capacity (such as Bottle Count, TLU, etc., as set in MDM settings).
• The route must have valid start and end times configured.

1. You can further refine your optimization by restricting trucks to specific scheduling areas or territories. Once you’re ready, click the green checkbox to start the optimization process.

1. After the initial optimization, if you want to make adjustments to the sliders or other settings to explore different outcomes, you can use the Rerun Fleet button. This allows you to reattempt the optimization without having to replot the data, speeding up the process by avoiding the need to recalculate distances and durations.
2. By using these tools effectively, you can optimize your fleet's performance, ensuring efficient and cost-effective routing.

For further details on Dynamic Fleet Optimization in Mango Mapping, please visit Chapter 17 of this manual:

Mango Mapping Manual- V8

Dynamic Fleet Optimization enables businesses to make data-driven decisions and adapt their fleet operations in real-time, resulting in improved efficiency, reduced costs, and enhanced performance. With the ability to optimize fleet allocation, scheduling, and routing based on changing conditions and business objectives, Dynamic Fleet Optimization is a valuable tool for businesses in transportation, logistics, and delivery industries, helping them stay competitive in a dynamic and fast-paced environment.