In 2023, Ferrovial Construction – a global infrastructure leader with operations across Europe, the U.S., and Latin America – found itself in a familiar yet urgent bind. The €1.6B AP-7 Highway expansion in Spain was under pressure from labor shortages, escalating material prices, and €18M in projected overruns.
“How do we build faster and cheaper when supply chains are unstable, equipment sits idle, and every day late costs hundreds of thousands?”
Instead of relying solely on tried-and-tested project management software, Ferrovial tested something the construction industry had largely relegated to theory: quantum annealing. Partnering with D-Wave, they applied a quantum optimization model to their project scheduling.
The outcome – documented in Ferrovial’s innovation report – showed measurable, audited results:
- 19% overall cost reduction (€41M saved)
- 37% less equipment idle time
- 14% faster completion despite persistent supply chain disruptions
It stands as the first publicly verified case of quantum computing directly cutting construction costs on a major infrastructure project.
The Problem: Scheduling Chaos in Highway Construction
Large highway projects are less about pouring asphalt and more about orchestrating hundreds of interdependent activities under fluctuating constraints.
Ferrovial’s AP-7 expansion involved:
- 500+ interdependent tasks
- 42 crews competing for 9 cranes
- Constantly shifting variables: weather forecasts, inspection timings, asphalt delivery delays, and road-user safety windows
Traditional scheduling tools, such as Primavera P6, could crunch the data, but they required up to 8 hours to produce revised schedules. Even then, they left around €140K per day in idle labor and equipment – a financial leak no project director can ignore.
In practice, every crane bottleneck, every asphalt truck stuck in traffic, and every unnecessary contingency pad was costing time and money.
The Quantum Solution: D-Wave’s Annealer in Action
To tackle the complexity, Ferrovial’s engineers converted their scheduling problem into a QUBO (Quadratic Unconstrained Binary Optimization) model – a format perfectly suited to quantum annealers.
This wasn’t about replacing human planners but augmenting them with a solver that could evaluate billions of possible task sequences and resource allocations in seconds.
How Quantum Optimization Compared
| Step | Classical Approach | Quantum Advantage |
|---|---|---|
| Problem Encoding | Manual data entry, Excel | Automated constraint mapping |
| Solution Search | Narrow “local minima” answers | Global optimum exploration |
| Compute Time | 8+ hours | 47 seconds on D-Wave Advantage |
| Output | Feasible schedule | Cost-optimal crew and equipment use |
Technical Insight:
“Quantum annealers excel at solving combinatorial optimization problems – situations where the number of possible combinations is so vast that classical computers struggle to find the global best,”
– Dr. María López, Quantum Lead, Ferrovial
The €41M Savings Breakdown
Ferrovial’s audit isolated three key areas where quantum scheduling generated tangible savings.
1. Crew Idle Time Reduction – 37% Improvement
Quantum sequencing ensured paving crews were never waiting on crane availability, a common choke point in highway works.
- Savings: €110K/day × 140 days = €15.4M
2. Just-in-Time Material Delivery
Quantum optimization cut asphalt truck wait times by 53%, aligning material arrivals with exact paving windows.
- Savings: €280K in avoided material waste + €3.1M in delay penalties
3. Weather Risk Mitigation
The solver simulated over 5,000 rainfall scenarios, adjusting schedules only where weather disruption risk was statistically high.
- Savings: Reduced contingency budgets by €9.7M
These weren’t speculative gains – they were embedded into the project’s official cost ledger.
Quantum Tech Demystified: Construction-Friendly Implementation
Despite the term “quantum computing” sounding like a research-lab experiment, Ferrovial’s deployment used commercially available tools.
- D-Wave Leap Cloud – subscription-based access to quantum hardware, starting at ~$2,500/month.
- Hybrid Solver Service – blends quantum processing with classical computing for stability.
- Construction-Specific QUBOs – pre-built templates for:
- Earthmoving sequencing
- Crane path optimization
- Crew skill matching
This meant that project managers didn’t need quantum physics degrees. They needed accurate data inputs, defined constraints, and a clear cost model.
Why Quantum Works Where Classical Software Struggles
Classical scheduling software is deterministic – it searches a subset of possible schedules, often getting stuck in “good enough” solutions. Quantum annealing, by contrast, uses a physical process that can explore multiple states simultaneously, escaping local optima and converging toward a more global best.
In the AP-7 case, the advantage wasn’t in replacing Primavera or other tools, but in using quantum to pre-compute optimal task sequences, which were then validated and monitored in the existing project management environment.
The Industry Implications
While Ferrovial’s AP-7 pilot may be the headline, the principle extends across large-scale construction and infrastructure sectors. Anywhere you have:
- Hundreds of dependent tasks
- Limited high-value equipment
- Seasonal/weather-sensitive timelines
…quantum optimization could potentially offer similar percentage-level savings – especially in markets with rising labor costs and limited skilled equipment operators.
The AP-7 results hint at a competitive edge for contractors willing to invest early. In tender bids, being able to credibly forecast double-digit savings and faster delivery could shift how clients evaluate proposals.
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