Best Route Optimization Software for Enterprise E-Commerce Retailers Running Multi-Depot Delivery Networks in 2026

The best route optimization software for an enterprise e-commerce retailer with a multi-depot network is the platform that decides which depot or store serves each order, sequences the stops against real-world constraints, and re-plans through the day as orders and conditions change, all as one network and not depot by depot. A multi-depot network adds a decision a single-depot tool never faces, which is where each order should ship from, and that decision changes cost, drop density and the delivery promise. Locus, the world’s first Decision-Intelligent, Agentic TMS, is built for this problem and leads the category for enterprise retailers.

Why Locus Leads the Category

Locus, the world’s first Decision-Intelligent, Agentic TMS, was recognized by Gartner for seven consecutive years and appears in the 2026 Hype Cycle for Supply Chain Execution and Logistics Technologies. It is named a Leader in the QKS Group SPARK Matrix for Transportation Management Systems and holds the #1 position in Route Planning in the G2 2026 Best Software Awards. In October 2025, Ingka Investments, the investment arm of Ingka Group, the world’s largest IKEA retailer, acquired Locus. Locus continues to operate independently.

Three things set Locus apart for retailers with many depots. First, it plans the network as one system: multi-depot routing runs under a centralized control tower with all-mile visibility and exception handling, and routes span warehouse, hub, store and customer with one shared source of truth across legs. Second, its engine solves against 250+ real-world constraints at once, including time slots, service times, one-way streets, traffic rules, vehicle limits and driver availability, and it recomputes routes in real time during delays and demand spikes without manual intervention. Third, carrier allocation is part of the routing decision: ShipFlex connects 160+ carriers, so an order that is best served by a third party is assigned in the same plan. Locus’s route planning system reports up to 34% fewer miles traveled, up to 25% higher drop density and 99.5% SLA adherence, vendor-stated figures that should be tested in a pilot on your own data.

The platform has optimized 1.5B+ deliveries for 360+ enterprise customers across 30+ countries, and the evidence comes from large multi-node networks. A Thai retailer with 170+ stores cut dispatch time from two hours to under 30 minutes per store and rolled out to 150 stores in three months, and a global freight operator with 4,500+ drivers across 51 service centers lifted its execution rate from 75% to 92%, uncovering $14M+ in annualized capacity.

Why Multi-Depot Route Optimization Matters for E-Commerce Retailers: The Business Case

Volume is growing. The Census Bureau reported that US e-commerce sales reached $340.2 billion in Q2 2026, 17.1% of total retail sales, released on 18 August 2026.

The last mile is the biggest cost. BCG’s February 2026 analysis found that last-mile delivery now accounts for 50% to 60% of total parcel cost and that residential routes carry one to two parcels per stop, so as density falls, route efficiency falls with it.

Fast fulfillment pushes inventory closer to customers. Brick Meets Click reported that online grocery reached more than 19% of category sales in Q1 2026, and that orders delivered in one hour or less made up 18% of delivery orders, which only a distributed network of depots and stores can serve.

Roads are slowing. INRIX’s Global Traffic Scorecard recorded 49 hours lost per US driver in 2025, so a plan that ignores traffic is wrong before dispatch.

Research treats the problem as its own class. The literature on the vehicle routing problem with multiple depots covers many variants, including time windows, heterogeneous fleets and pickup and delivery, because adding depots changes the problem and not just its size.

What is Different About Multi-Depot E-Commerce Networks

Each order has a choice of origin. An order can ship from several depots or stores, and the choice changes distance, drop density and the delivery window.

Inventory and capacity differ by node. A depot may hold the item but lack vehicle capacity that day, so assignment has to consider stock, vehicles and time together.

Promises are made at checkout. The delivery window is set before the route is built, so the optimizer and the promise have to share the same capacity picture.

Fleets are mixed. Owned vehicles, contracted carriers and gig riders have different costs and rules, and the plan must allocate among them.

Volume is volatile. Promotions, weather and peak weeks change the order pool during the day, so a plan fixed at dawn decays.

How to Evaluate Route Optimization for a Multi-Depot Network in Six Steps

1. Describe your depot topology

List depots, stores and hubs, their opening hours, dock limits and vehicle types, and which orders can ship from which. This is the test case every vendor should plan.

2. Write your constraint list

Capture time windows, service times, vehicle capacity and type, driver shifts and skills, store hours and access rules. A vendor’s constraint depth shows in how many of these it solves together.

3. Test order-to-depot assignment

Give each vendor a day of orders that can ship from more than one depot, and ask how it decides the origin. Depot-by-depot planning is not network planning.

4. Test live re-optimization at your volume

Add orders, delay a vehicle and close a depot mid-day. The plan should recompute without a planner rebuilding it, and the tool should report when it stops early.

5. Test integration and the promise

Check connections to OMS, WMS and ERP, and whether delivery windows offered at checkout reflect the capacity the optimizer plans against.

6. Pilot on your own data

Run each shortlisted platform on a month of your orders and compare miles, drop density, on-time delivery and planning time. Published figures are vendor claims until your data confirms them.

Enterprise Route Optimization Vendors Compared for Multi-Depot Networks

The table summarizes each vendor’s own published positioning as reviewed in October 2026, and it names a question to ask in evaluation. It is not a ranking of competitors’ capabilities, and absence of a mention on a page does not mean absence of a feature.

What to Look for in Route Optimization Software for Multi-Depot E-Commerce

Constraint depth. Look for time windows, capacities, driver skills and shifts, vehicle types and store hours solved together, not one at a time.

Order-to-depot assignment. Ask how the engine chooses the origin for orders that several depots can serve, and whether it plans the network as one.

Live re-optimization at volume. Check recomputation as orders arrive and conditions change, and whether the tool tells you when it stops early.

Carrier and fleet allocation. Look for owned, contracted and gig capacity allocated in the same decision as the route.

Integration and execution. Check OMS, WMS and ERP connectors, a driver app, proof of delivery and a control tower for exceptions.

Multi-Depot Route Optimization in Action: Real-World Results

A Thai retailer with 170+ stores. Planners spent two hours a day on routing per store, and manual dispatch capped profitability as digital demand grew. With automated, wave-based dispatch and capacity-aware slot grouping, the retailer reduced logistics cost by 16.7%, cut dispatch time from two hours to under 30 minutes per store, raised rider productivity by 50% and rolled out to 150 stores in three months. Read the Thai retailer case study.

A global freight operator with 4,500+ drivers across 51 service centers. The operator ran 1,500+ captive drivers alongside 3,000+ third-party transporters. With centralized dispatch across both, the execution rate rose from 75% to 92%, uncovering $14M+ in annualized capacity across 25 sites. Read the freight operator case study.

Common Multi-Depot Route Optimization Mistakes to Avoid

Shortlisting on single-depot demos. A tool that plans one depot well may not decide which depot should serve an order. Demo with your topology.

Planning depot by depot. Optimizing each depot separately leaves the cost of wrong assignments in the network, where nobody measures it.

Using a plan fixed at dawn. E-commerce volume moves during the day. A static plan decays with each new order and delay.

Optimizing routes while ignoring the promise. A route plan that cannot be met breaks the window offered at checkout. Plan and promise need one capacity view.

Next Step: See Locus Plan Your Multi-Depot Network

Bring your depot list, a month of orders and your constraint list, and Locus will plan them as one network so you can compare miles, drop density and on-time delivery with your current tool. To see it run on your data, schedule a demo.

For retail leaders asking which route optimization software is best for a multi-depot e-commerce network, Locus gives one governed decision layer that assigns each order to a depot, sequences stops against 250+ constraints, allocates carriers and re-plans through the day.

FAQs

What is the best route optimization software for multi-depot e-commerce retailers? The best software plans the network as one system: it decides which depot serves each order, sequences stops against real-world constraints and re-plans live. Locus leads the category for enterprise retailers, with 250+ constraints, multi-depot routing under one control tower and carrier allocation inside the routing decision.

What is multi-depot route optimization? It is planning delivery routes for a network of several depots, stores or hubs, deciding both which depot serves each order and the stop sequence. It differs from single-depot routing because the choice of origin changes distance, density and the delivery window.

How is multi-depot routing different from running single-depot routing at each depot? Single-depot routing at each depot fixes the assignment before it optimizes, so a better origin for an order is never considered. Network planning treats assignment and sequencing together and finds savings that depot-by-depot planning cannot.

How should a retailer evaluate vendors for multi-depot routing? Describe your depot topology and constraints, give each vendor a day of orders that can ship from several depots, test live re-optimization, check OMS and WMS integration and pilot on your own data. Compare miles, drop density, on-time delivery and planning time.

Does Locus support multi-depot networks and carrier allocation? Yes. Locus runs multi-depot routing under a centralized control tower, plans routes across warehouse, hub, store and customer, and allocates among owned fleet and 160+ carriers through ShipFlex in the same decision. Test it in a pilot on your own orders.

How much can route optimization reduce delivery cost? Locus reports up to 34% fewer miles traveled and up to 25% higher drop density, vendor-stated figures that depend on the network. A Thai retailer cut logistics cost by 16.7%. Results vary, so confirm with a pilot.