Travel time and route optimization

Overview

Route planning can be complicated, especially when you need to account for multiple parameters and constraints. Often we need to take into account the most optimal distance and travel time parameters of the jobs within optimizations.

Skedulo’s route optimization algorithm can quickly and automatically solve virtually any variations of the most difficult routing problems – such as the Traveling Salesman Problem (TSP) and the Vehicle Route Problem (VRP).

How do we do this?

Provided we have the resource’s home address and the addresses for the jobs that need to be optimized, the optimizer can determine a feasible solution based on one of the following scheduling goals:

• Minimize the travel time for resources.
• Minimize the number of resources used to deliver the work.
• Balance the work across resources.

Optimization using geoservices

Skedulo uses geoservices to provide the most efficient and accurate travel estimates when constructing the schedule.

Geoservices are a critical component of route optimization. Route optimization utilizes distance matrices that have distance and travel time between locations. This allows the optimizer to efficiently factor time and or distance in the evaluation of solutions.

How do we calculate travel time for optimized schedules?

Skedulo’s optimization capabilities are paired with the introduction of historical traffic patterns for travel time and distance.

Distance may change with the time of day because the fastest route may change depending on traffic. Without traffic information, we likely generate schedules that cannot be achieved in metropolitan areas.

This provides more accurate travel estimates when constructing the schedule and determining feasible solutions. For example, travel time is considered where there is a set maximum amount of travel time, or when determining whether or not it is possible for a resource to travel between one job and another in time.

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