Mathematical Optimization & Machine Learning

LityxIQ Solutions

LityxIQ has uniquely integrated a solver for mixed-integer programming so that mathematical optimization can be performed on our clients’ most complex business problems.

Mathematical optimization complements machine learning-based predictions by optimizing the decisions that businesses make. It allows firms to model the key features of a complex real-world problem that must be considered to make the best possible decisions and provides business benefits.

Identify the path of least resistance while understanding the impact of individual requirements.

Hidden within complex processes are opportunities to make better decisions.

Hidden within complex processes are wasteful steps, options and outcomes.

Be smarter, faster, more efficient and effective than your competitors.

“With Al and ML adoption on the rise, Mathematical Optimization is poised to become the decision-making executor for ML solutions that involve precious enterprise resources.” —Forrester

LityxIQ Target Uses for Optimization

  • Operational applications
  • Business processes
  • Logisitics
  • Scheduling
  • Routing
  • Resource optimization

  • Pricing

  • Planning

  • Customer experience

  • Supply chain planning

LityxIQ Business Deliverables

Estimation of Impact

Top Predictors Profile Report

Model(s) Performance

Recommendation

Scenarios

Portrait Of Senior Friends Hiking In Countryside

As part of the ongoing effort to bring on new members, the Alternative Marketing team at AARP had a lengthy, complex, and arduous monthly campaign selection process due to the use of multiple channels with geographic, supplier, audience, and budget requirements and targeting options. Learn how Lityx helped create an over 90% improvement in acquisition rates at a lower cost-per-acquisition and more.

Read Our AARP Case Study

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