Network Design

Open the right facilities in the right places

Location decisions lock in costs for years. Wrong placement means excess transport costs, poor coverage, and stranded inventory.

16% cost reduction

The problem

Why this decision becomes expensive without structure

Location decisions lock in costs for years. Wrong placement means excess transport costs, poor coverage, and stranded inventory.

Spreadsheets and manual planning break down when constraints interact. Generic AI tools lack the structural matching needed to produce usable, reviewable outputs. This use case needs a decision workflow that fits the problem shape, not a one-size-fits-all answer.

Typical use cases

Where this solution fits

Choose which candidate warehouse sites to open

Design hub-and-spoke distribution networks

Place EV charging stations for maximum coverage

Evaluate facility closure scenarios

Outputs you receive

Decision-ready outputs for this use case

Mongeflow packages this work into stakeholder-ready output layers and premium export formats.

Optimal location recommendations
Cost-coverage tradeoff analysis
Scenario comparison (open/close)
Network flow visualization

Benchmark context

16% cost reduction

Ernst et al. (2004) EJOR

Where this solution is used

Related industries

RetailLogisticsHealthcareEnergy

See this workflow inside Mongeflow

Explore how Mongeflow turns this operational problem into a structured decision path with clearer outputs, assumptions, and handoff.