Start with the locations.
See the stores across the Southside and Peninsula, then consider how Newport News and Suffolk distribution centers serve that network.
Explore the store-location map →MODELING, MAPPING & VISUALIZATION
From a location network to a calculated plan.
Our fictional supplier, Tidewater Candy Supply, delivers cases of Snickers and Reese’s cups to 92 grocery locations across Hampton Roads. Two distribution centers have five days to complete the deliveries. The demonstration connects the geography, operating constraints, and calculated alternatives.
Make the constraints explicit.
Set whole-case product demand, DC stock, truck capacity, service time, and a five-day delivery window. Each store receives one complete order.
Inspect the scenario assumptions →Understand the tradeoffs.
Switch scenarios and compare initial and best-found plans. Inspect the routes, loads, remaining inventory, and modeled delivery cost.
Explore the calculated plans →Stores supplied—One complete delivery each
Cases delivered——
Modeled route miles—Straight-line distance proxy
Modeled delivery cost——
Vehicle-days used——
◆ Distribution center · ● Grocery stopSchematic connections, not driving routes
FOLLOW THE DELIVERY
Choose a route to inspect its stops.
Select a route from the list or map.
SUPPLY → DEMAND
Weekly DC inventory
Whole cases; fixed stock, with no replenishment or transfers during the week.
FIVE-DAY DELIVERY WINDOW
Weekly schedule
Delivery days are interchangeable here. Solved routes are spread across available weekday truck slots; daily workload balance is not optimized.
| Day | Routes | Stores | Cases | Modeled miles | Route hours |
|---|
SAME INPUTS, TWO PLANS
What the search improved
Each scenario compares its first feasible solver plan with the best plan retained after further search. Comparisons use the same demand, stock, fleet, and constraints.
| Scenario | Cases | Initial cost | Best cost found | Cost reduction | Vehicle-days |
|---|
From model to map
01 / Define
Public store geography plus fictional product demand, stock, fleet, and operating rules.
02 / Calculate
The optimizer runs offline and exports validated plans.
03 / Explore
This page displays saved outputs. Selecting a scenario changes the visuals; it does not run a live solver.
OPTIMIZATION FOR YOUR OPERATION
Build the model around your business.
SOLLUS provides complex supply chain and operational optimization services tailored to each client. We translate operating objectives and real constraints into models, calculate feasible alternatives, and make the tradeoffs clear enough to act on.
Supply & allocation
Evaluate how inventory and distribution capacity should support demand across locations.
Routes & resources
Model delivery networks, vehicle capacity, staffing, and scheduling constraints.
Operational scenarios
Compare demand shifts, capacity changes, and alternative operating policies before committing resources.
Start with the decision you need to make, the limits you operate within, and the outcomes that matter.
Discuss your optimization project →This demonstration is a fictional SOLLUS project, not a client engagement or a claim of realized savings. Store geography comes from a saved, partial public-locator snapshot. Business inputs are illustrative; the current model uses straight-line travel estimates and does not establish global optimality.