Housing Allocation Networks and Graph Optimization

Data-driven allocation can match people to homes based on need and reduce waste, without treating housing as a bidding war.

Housing markets often allocate space through price alone, which is inefficient when demand is inelastic and supply is constrained. You can do better with allocation networks that match people to housing based on needs and constraints.

The Allocation Concept

Imagine a system where you provide your needs: location, size, accessibility, budget, and community preferences. The system maps housing stock and matches people to homes using optimization methods. It seeks the highest overall fit rather than the highest bid.

Why It Improves Outcomes

The Human Layer

This is not a rigid assignment. You can still choose, but you choose within a system designed to maximize fit and reduce waste. It is similar to how infrastructure planning already works: design for flow, not for individual bidding wars.

Integration with Decommodification

Allocation networks are most powerful when housing is not a speculative asset. When prices are stable and access is guaranteed, optimization becomes a tool for fairness and efficiency rather than a mechanism for exclusion.

The Vision

You spend less time hunting and more time living. Housing becomes a coordinated system that adapts to real life, not a chaotic scramble for scarce listings.

Part of Decommodified Shelter