Intelligent retail logistics: a routing service for the italian large-scale grocery

Integrating AI as a Service into Tesisquare’s TMS for optimised trip planning.

Markets

Solutions

Routing as a Service

The challenge

Major food retail networks face the daily logistical challenge of planning complex transport operations to hundreds of stores.

Technology partner Tesisquare brought in Optit to overcome the limitations of traditional optimisation engines, which have long suffered from fragmented workflows, lengthy calculation times and constant manual corrections by planners.

The challenge was to enable the retailer to manage the planning of transfers between depots, clearly separating deliveries to warehouses from those destined for stores. The process had to be centralised to guarantee maximum fleet utilisation and full compliance with delivery time windows, while keeping after-the-fact changes to a minimum.

How we create value

Optit’s response was to integrate the standard version of its routing model for the retail sector directly into Tesisquare’s TMS. The integration was delivered as a “black box” (AI as a Service) via API, allowing planners to harness the power of the optimisation engine straight from their familiar software interface.

At the heart of the solution is an iterative mathematical algorithm that works through sequential phases: pre-processing to check that orders can be planned, probabilistic cycles of destruction and reconstruction of the solution to explore the best alternatives, and a final post-processing step to calculate KPIs.

The model evaluates trip plans against a clear hierarchy of priorities (meeting demand, minimising costs and the number of vehicles), natively handling complex constraints such as multi-trip logic and multi-dimensional capacity (pallets, kilos and cubic metres).

Impact

The algorithm developed by Optit makes it possible to manage the entire daily planning process with a single automated run for each departure depot. Results and supply chain performance are measured directly through structured KPIs:

Optimisation of the number of trips per planning area.
Maximisation of the average vehicle fill rate across the plan.
Minimisation of the total number of vehicles used.

A drastic reduction in calculation times and manual changes.