MODAct Benchmarks

The MODAct (Multi-Objective Design of electro-mechanical Actuators) benchmark collection includes 20 benchmark problems for constrained multi-objective optimization.

Available Problems

  • bocode.Engineering.MODAct.CS1

  • bocode.Engineering.MODAct.CT1

  • bocode.Engineering.MODAct.CTS1

  • bocode.Engineering.MODAct.CTSE1

  • bocode.Engineering.MODAct.CTSEI1

  • bocode.Engineering.MODAct.CS2

  • bocode.Engineering.MODAct.CT2

  • bocode.Engineering.MODAct.CTS2

  • bocode.Engineering.MODAct.CTSE2

  • bocode.Engineering.MODAct.CTSEI2

  • bocode.Engineering.MODAct.CS3

  • bocode.Engineering.MODAct.CT3

  • bocode.Engineering.MODAct.CTS3

  • bocode.Engineering.MODAct.CTSE3

  • bocode.Engineering.MODAct.CTSEI3

  • bocode.Engineering.MODAct.CS4

  • bocode.Engineering.MODAct.CT4

  • bocode.Engineering.MODAct.CTS4

  • bocode.Engineering.MODAct.CTSE4

  • bocode.Engineering.MODAct.CTSEI4

Example Usage

import bocode
import torch

# Create a MODAct benchmark problem
problem = bocode.Engineering.MODAct.CS1()

# Evaluate at a point
x = torch.tensor([[0.5] * problem.dim])
values, constraints = problem.evaluate(x)

print(f"CS1 objective function values at [0.5]*dim: {values[0]}")

Output:

CS1 objective function values at [0.5]*dim: tensor([0.3887, -50.4243])