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Generative Design for Infrastructure

Use advanced algorithms to explore, evaluate, and optimize design alternatives based on cost, performance, and sustainability objectives

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Infrastructure design decisions are often made by evaluating a limited number of alternatives, restricting the ability to balance cost, performance, and sustainability in increasingly complex projects

WHY THIS “GENERATIVE DESIGN FOR INFRASTRUCTURE” CHALLENGE?

Design outcomes are constrained by how many options can realistically be explored

Time, cost, and engineering effort typically limit analysis to a small set of scenarios, making it difficult to fully understand trade-offs or identify higher-performing design solutions

Key benefits

Expanding design exploration to improve outcomes

More options, better trade-offs, stronger decisions

Exploration of thousands of design alternatives

Generate and evaluate a wide solution space beyond what manual approaches can cover

Optimization across multiple criteria

Balance cost, performance, and sustainability simultaneously within defined constraints

Faster evaluation and decision cycles

Reduce time spent analyzing alternatives while increasing depth of insight

Improved consistency and quality of designs

Use structured algorithms to support repeatable and transparent decision-making.

How NTT DATA helps

01

Defining design objectives and constraints

Establish clear parameters to guide algorithm-driven exploration

02

Integrating relevant input data

Incorporate geometry, topography, materials, and cost variables into the models

03

Developing parametric and generative algorithms

Build models capable of producing and evaluating multiple design scenarios

04

Automating evaluation of alternatives

Assess performance across criteria to identify optimal solutions

05

Integrating outputs into engineering workflows

Connect results with BIM models, cost estimation, and reporting processes

Proven impact

Enabling engineering teams to identify higher-performing design solutions by systematically exploring and evaluating a broader range of alternatives

Results that matter

Measurable improvements in design efficiency, cost, and decision quality:

Reduced time to evaluate design alternatives

Automation accelerates analysis without compromising depth

Lower construction and lifecycle costs

Optimization identifies more cost-efficient solutions early in the process

Reduced environmental impact

Sustainability criteria are embedded directly into design decisions

Better-informed and traceable decisions

Structured evaluation improves transparency and confidence in outcomes

Explore more design alternatives to identify optimal infrastructure solutions

Improve performance, cost, and sustainability outcomes

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