Package org.moeaframework.problem.BBOB2016
package org.moeaframework.problem.BBOB2016
Package containing the BBOB 2016 biobjective test problems. These problems will be tested in the Workshop on
RealParameter BlackBox Optimization Benchmarking at GECCO 2016. The authors combine various singleobjective
functions to form the biobjective test suite. Each of the singleobjective functions has wellknown problem
properties, including looking at the conditioning number. Conditioning looks at the effect of small changes to the
function's inputs on its output. For example, small changes to a low conditioned function causes only small changes
in the output.
Note: this implementation does not provide all BBOB test functions. It currently only implements the 55 test functions studied in the bbobbiobj suite.
References:
 Coco Github page
 Finck, S., N. Hansen, R. Ros, and A. Auger. "RealParameter BlackBox Optimization Benchmarking 2010: Presentation of the Noiseless Functions." Working Paper 2009/20, compiled November 17, 2015. (PDF)
 http://numbbo.github.io/cocodoc/bbobbiobj/functions/
 https://arxiv.org/abs/1604.00359

ClassDescriptionThe Attractive Sector function.Problem provider for all problems in the BBOB 2016 test suite.Abstract class for the functions provided by the BBOB test suite.Abstract class for transformations provided by the BBOB test suite.The Different Powers function.The Ellipsoid function.The 101peak Gallagher function.The Rastrigin function.The Rosenbrock function.The Schaffers F7 function.The Schwefel function.The Sharp Ridge function.The sphere function.Combines two or more singleobjective
BBOBFunction
s into a multiobjective problem.Transformation that oscillates the objective values of the inner function.Transformation that penalizes the objectives if the decision variables fall outside the region of interest.Transformation that raises the objective value to the power of a given exponent.Transformation that offsets the value of the objective by a fixed amount.Performs an affine transformation of the form f(x) = Mx + b.Transformation used to convert a symmetric to an asymmetric decision space.Transformation that skews or scales the decision variables using the same method described by the BucheRastrigin function.Transformation that alters the condition number of the function.Transformation that applies a monotone oscillation to the decision variables of the inner function.Transformation that scales the decision variables by a given factor.Transformation that shifts all decision variables by a given offset.The xhat transformation, which negates some of the decision variables.The zhat transformation used by the Schwefel function.