Reshaping Industries with Agent-Driven Multi-Objective Optimization
Welcome to the Future of Multi-Objective Optimization with globalMOO
globalMOO's Innovative AI Solutions Reshape Efficiency in Energy, Manufacturing, Supply Chain, Environmental Engineering, Aerospace, and Healthcare
Revolutionizing Industry Standards Across Diverse Sectors
Transforming Logistics
Impact Factor Calculation Technology
globalMOO's Commitment to Excellence and Innovation in Optimization
Benchmarking
Multi-Objective Optimization Comparisons
globalMOO Outperforms Competitors in Efficiency and Speed Across All Tests
Comparing up to 32 Input Parameters
In this example, up to 32 input parameters with various output parameters were compared. The scale of the plot is logarithmic and and each dashed line represents an order of magnitude increase in iterations (or run time). For various sample problems MOEAD, DNSGA2 need up to 100,000 iterations to solve a 30 variable problem. globalMOO requires less than 100 iterations for optimization, using up to 1000 training cases. This means, once the training is complete, it can be used for achieving other targets and objectives with less than 100 iterations. That’s 1000 times fewer iterations than over available solutions.
MaxCut Problem – Drilling a Circuit Board
globalMOO Outperforms Competitors in Efficiency and Speed Across All Tests
globalMOO vs. Google OR Tool: Superior Efficiency in Circuit Board Drilling
The figure on the left compares the paths that globalMOO and Google OR Tool calculate for a circuit board with 280 holes. globalMOO drills the 280 holes in a shorter distance than the Google OR Tool, finding a more efficient path that takes less time and doesn’t cross its own path.