Package org.moeaframework.problem
Interface AnalyticalProblem
- All Superinterfaces:
AutoCloseable,Named,Problem
- All Known Implementing Classes:
Binh,Binh4,C1_DTLZ1,C1_DTLZ3,C2_DTLZ2,C3_DTLZ1,C3_DTLZ4,ConvexC2_DTLZ2,ConvexDTLZ2,DTLZ1,DTLZ2,DTLZ3,DTLZ4,DTLZ5,DTLZ6,DTLZ7,Fonseca,Fonseca2,InvertedDTLZ1,Jimenez,Laumanns,MaF1,MaF10,MaF11,MaF12,MaF13,MaF14,MaF15,MaF3,MaF4,MaF5,MaF6,MaF7,MaF8,MaF9,Murata,Obayashi,Rendon2,Schaffer,Schaffer2,UF13,WFG,WFG1,WFG2,WFG3,WFG4,WFG5,WFG6,WFG7,WFG8,WFG9,ZCAT,ZCAT1,ZCAT10,ZCAT11,ZCAT12,ZCAT13,ZCAT14,ZCAT15,ZCAT16,ZCAT17,ZCAT18,ZCAT19,ZCAT2,ZCAT20,ZCAT3,ZCAT4,ZCAT5,ZCAT6,ZCAT7,ZCAT8,ZCAT9
Interface for problems whose Pareto optimal set is known analytically, providing the
generate() method for
producing randomly-generated reference sets.-
Method Summary
Methods inherited from interface org.moeaframework.problem.Problem
close, evaluate, getName, getNumberOfConstraints, getNumberOfObjectives, getNumberOfVariables, isType, newSolution
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Method Details
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generate
Solution generate()Returns a randomly-generated solution using the analytical solution to this problem. The exact behavior of this method depends on the implementation, but in general (1) the solutions should be non-dominated and (2) spread uniformly across the Pareto front.It is not always possible to guarantee these conditions. For example, a discontinuous / disconnected Pareto surface could generate dominated solutions, and a biased problem could result in non-uniform distributions. Therefore, we recommend callers filter solutions through a
NondominatedPopulation, in particular one that maintains a spread of solutions.Furthermore, some implementations may not provide the corresponding decision variables for the solution. These implementations should indicate this by returning a solution with
0decision variables.- Returns:
- a randomly-generated Pareto optimal solution to this problem
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