Package org.moeaframework.problem.LSMOP

package org.moeaframework.problem.LSMOP
Package for the scalable LSMOP test problem suite.

These codes are based on the Matlab source code provided by the authors. Additionally, we use the Matlab source to generate the test results: 

   Population = LSMOP('init', 'LSMOP1', 2, 10)
   [ps,D] = size(Population)
   LSMOP('fitness', 'LSMOP1', 2, 0.5 * ones(1,D))   % Evaluate solution (0.5, 0.5, ..., 0.5)
and the Pareto Fronts: 
 
   PF = LSMOP('PF', 'LSMOP1', 2, 100)
   writematrix(PF,'LSMOP1.2D.pf','Delimiter',' ','FileType','text')
References:
  1. Ran Cheng, Yaochu Jin, Markus Olhofer and Bernhard Sendhoff. "Test problems for large-scale multiobjective and many-objective optimization." IEEE Transactions on Cybernetics, 7(12): 4108-4121, 2017.
  2. Supplementary Materials available at http://www.soft-computing.de/jin-pub_year.html
  • Class
    Description
    CorrelationMatrix
    Correlation matrices used by the LSMOP test problem suite.
    LinkageFunction
    Linkage functions used by the LSMOP test problem suite.
    LSMOP
    Abstract class for defining LSMOP test problems.
    LSMOP1
    The unimodal, fully-separable LSMOP1 problem.
    LSMOP2
    The mixed-modality, partially-separable LSMOP2 problem.
    LSMOP3
    The multi-modal, mixed-separability LSMOP3 problem.
    LSMOP4
    The mixed-modality, mixed-separability LSMOP4 problem.
    LSMOP5
    The unimodal, fully-separable LSMOP5 problem.
    LSMOP6
    The mixed-modality, partially-separable LSMOP6 problem.
    LSMOP7
    The multi-modal, mixed-separability LSMOP7 problem.
    LSMOP8
    The mixed-modality, mixed-separability LSMOP8 problem.
    LSMOP9
    The mixed-modality, fully-separable LSMOP9 problem.
    LSMOPProblemProvider
    Problem provider for the LSMOP test problems.
    ParetoFrontGeometry
    Functions specifying the Pareto Front geometry for the LSMOP test problem suite.
    ShapeFunction
    Shape functions used by the LSMOP test problem suite.