generateMOP: MOP test function generator.
In danielhorn/moobench: Multi Objective Optimization Benchmark Functions

Description Usage Arguments Value References

MOP test function generator.

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generateMOP(id, in.dim = 30L, out.dim = 2L)

generateMOP_C(id, in.dim = 30L, out.dim = 2L, on.infeasible = "stop")

`id`	[`integer(1)`] Which MOP function? Valid values are 1, 2, ..., 7. Which MOP_C function? Valid values are 1, 2, 3.
`in.dim`	[`integer(1)`] Size of parameter space. Specified for each MOP function.
`out.dim`	[`integer(1)`] Size of target space. Specified for each MOP function.
`on.infeasible`	[`character`] What should happen if infeasible values are evaluated? Possible values are stop (code stops with error message) and NA (NA value is returned).

A mooFunction.

OHD. A. Van Veldhuizen, “Multiobjective Evolutionary Algorithms: Classifications, Analyzes, and New Innovations,” Ph.D. Dissertation, Air Force Institute of Technology, Wright-Patterson AFB, Jun. 1999.

danielhorn/moobench documentation built on May 14, 2019, 4:04 p.m.