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  • Writer's pictureSimon Webb

Understanding Optimisation Objectives in Tarot Routing

Optimisation Objectives

Effective delivery management is crucial for businesses looking to streamline operations and improve customer satisfaction. Tarot Routing offers the flexibility to optimise delivery routes based on three different objectives: Time, Distance, and Cost. Each optimisation objective serves specific needs and use cases, and understanding these can help businesses select the best option for their operations.

Time Optimisation

When Time is selected as the optimisation objective, the algorithm seeks to minimise driving time across the fleet. This is the default optimisation setting and is suitable for most users. Time optimisation focuses on creating the fastest possible routes, often favouring major roads, highways, and toll roads.


  • Enhanced Customer Satisfaction: Faster deliveries can lead to happier customers and repeat business.

  • Increased Delivery Capacity: Less time driving on each route allows drivers to complete more deliveries in a day.


  • Driver Utilisation: Some drivers may be allocated little or no work, or expensive drivers may be allocated more work than cheaper drivers.

  • Other Route Costs: Speedier routes might require toll roads or longer distances.

Distance Optimisation

When Distance is selected as the optimisation objective, the algorithm aims to minimise kilometres driven across the fleet. This option is ideal for reducing wear and tear on vehicles and lowering environmental impact. It is particularly suited for deliveries over large areas, fleets with high cost per kilometre (such as larger trucks), or operations in regions with many toll roads (e.g. Sydney, Australia).


  • Reduced Fuel and Maintenance Costs: Shorter distances mean less fuel consumption and lower vehicle wear and tear.

  • Lower Environmental Impact: Fewer kilometres driven contributes to reducing the carbon footprint.


  • Longer Working Hours & Delivery Times: Shortest routes aren't always the fastest, which might affect working hours and delivery times.

Cost Optimisation

When Cost is selected as the optimisation objective, the algorithm seeks to minimise the monetary cost across the fleet. This objective is more complex and requires additional data input, such as defined billing rates for each driver. However, it can provide better results when set up correctly, especially for mixed fleet use cases.


  • Cost Efficiency: Allocates more work to lower-cost resources, optimising overall expenditure.

  • Balanced Workload: Ensures better utilisation of all vehicles and drivers based on cost efficiency.


  • Setup and Data Requirements: Billing rates and accurate costing information needs to be setup in Tarot Routing to feed optimisaiton algorithm. Setting up and tuning these parameters can be difficult for a new user.

Choosing the Right Optimisation Objective

Selecting the appropriate optimisation objective depends on specific use cases:

  • Time Optimisation: Best for applications prioritising quick deliveries and customer satisfaction.

  • Distance Optimisation: Ideal for large delivery areas, high per-kilometre costs, or areas with many toll roads.

  • Cost Optimisation: Suited for mixed fleet operations, balancing employee and contractor costs, and fleets with varied vehicle sizes.

By understanding the strengths and considerations of each optimisation objective, businesses can make informed decisions that align with their operational goals and constraints.

Tarot Routing’s flexible optimisation objectives empower businesses to tailor their delivery operations to meet unique needs. To learn more about optimising delivery routes with Tarot Routing, request a demo today and see the difference customisable optimisation objectives can make for your business.


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