import pymop.problems pymop.problems.Rastrigin().evaluate([-5.12]*2)

pymop - Multi-Objective Optimization Problems

This framework provides a collection of test problems in Python. The main features are:

• Most important multi-objective test function is one place
• Vectorized evaluation by using numpy matrices (no for loops)
• Gradients and Hessian matrices are available through automatic differentiation
• Easily new problems can be created using custom classes or functions

Here, you can find a detailed documentation and information about the framework: https://www.egr.msu.edu/coinlab/blankjul/pymop/

Problems

In this package single- as well as multi-objective test problems are included:

• Single-Objective:
  • Ackley
  • Cantilevered Beam
  • Griewank
  • Himmelblau
  • Knapsack
  • Pressure Vessel
  • Schwefel
  • Sphere
  • Zakharov
  • G1-10
• Multi-Objective:
  • ZDT 1-6
  • CTP
  • Carside Impact
  • BNH
  • Kursawe
  • OSY
  • TNK
  • Truss 2D
  • Welded Beam
• Many-Objective:
  • DTLZ 1-7
  • CDTLZ