CEC 2007 Benchmarks

The CEC2007 benchmark collection contains all functions from the CEC 2007 Competition. More information can be found in the CEC 2007 GitHub page.

Sources:

    1. Huang, A. K. Qin, K. Deb, E. Zitzler, P. N. Suganthan, J. J. Liang, M. Preuss and S. Huband (2007). Problem Definitions for Performance Assessment of Multi-objective Optimization Algorithms. Special Session on Constrained Real-Parameter Optimization, Technical Report, Nanyang Technological University, Singapore, 2007. https://github.com/P-N-Suganthan/CEC2007/blob/master/CEC-07-TR-13-Feb.pdf

Simon Wessing. Towards Optimal Parameterizations of the S-Metric Selection Evolutionary Multi-Objective Algorithm. Diploma thesis, Algorithm Engineering Report TR09-2-006, Technische Universitaet Dortmund, 2009. https://ls11-www.cs.uni-dortmund.de/_media/techreports/tr09-06.pdf

Available Problems

  • bocode.CEC.CEC2007.CEC2007_OKA2

  • bocode.CEC.CEC2007.CEC2007_R_DTLZ2

  • bocode.CEC.CEC2007.CEC2007_R_ZDT4

  • bocode.CEC.CEC2007.CEC2007_SYMPART

  • bocode.CEC.CEC2007.CEC2007_S_DTLZ2

  • bocode.CEC.CEC2007.CEC2007_S_DTLZ3

  • bocode.CEC.CEC2007.CEC2007_S_ZDT1

  • bocode.CEC.CEC2007.CEC2007_S_ZDT2

  • bocode.CEC.CEC2007.CEC2007_S_ZDT4

  • bocode.CEC.CEC2007.CEC2007_S_ZDT6

  • bocode.CEC.CEC2007.CEC2007_WFG1

  • bocode.CEC.CEC2007.CEC2007_WFG8

  • bocode.CEC.CEC2007.CEC2007_WFG9

Example Usage

import bocode
import torch

# Create a Botorch benchmark problem
problem = bocode.CEC.CEC2007.CEC2007_OKA2()

# Get problem information
bounds = problem.bounds

# Evaluate at a point
x = torch.Tensor([[0.0] * problem.dim])
values, constraints = problem.evaluate(x)

print(f"OKA2 function value at origin: {values[0]}")

Output:

OKA2 function value at origin: tensor([0.0000, 2.4600])