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The primary concerns for customers utilizing a Vehicle Routing Problem (VRP) solver typically revolve around three key aspects: fast computational time, visually appealing clustered routes, and optimization for cost efficiency. Striking a balance among these factors is often challenging.

in this blog post, we will explore all the pons and cons of the origin-destination routing matrix (OD matrix) options out there on the market.

What is the trade-off between optimality and speed? And how much does speed impact optimality, and vice versa?

Route optimization software quality is not only about the operating cost but also the visualization of the generated route plans.

At LogisticsOS, we have developed a cost optimization engine into our API, empowering delivery platforms to further reduce their shipping expenses.

The ultimate goal of the route optimization API is to reduce last-mile delivery costs.

Expand on the existing scalable automated dispatch and take it to the next level with the versatility, flexibility and capabilities offered by LogisticsOS.

With the high demand and expectations for delivery services, businesses often feel the pain of scaling up their services and improving the order ETAs. When it comes to route optimization and fleet dispatching, few solutions are truly able to scale with the increasing volume and demand.

Small and large businesses alike rely on route optimization software to help save them time and money across the entire delivery process. But with all of the mainstream platforms on the market, choosing the right product for your business can be difficult.

Route optimization engines are a dime a dozen, with quite a few famous open-source products out there. These proprietary solutions developed by last-mile techs from billion dollar companies and startups alike are typically built on top of open-source projects.

Cut delivery cost. Handle more on-demand volume in real-time.