mooFunction: Multi Objective Optimization Function
In danielhorn/moobench: Multi Objective Optimization Benchmark Functions

Define a new mooFunction object.

1 2	mooFunction(name, id, fun, in.dim, out.dim, param.set, paretoSet, paretoFront, on.infeasible = "stop")

`name`	[`character(1)`] Name of function.
`id`	[`character(1)`] Short id for the function. Must be unique to the function instance and should not contain any other characters than [a-z], [0-9] and ‘-’.
`fun`	[`function`] Function definition. Must have a single parameter x.
`in.dim`	[`integer(1)`] Size of paramter space.
`out.dim`	[`integer(1)`] Dimnesion of the targer space.
`param.set`	[`ParamSet`] Parameter set to describe (box) constraints for the function.
`paretoSet`	[`function` \| NULL] Function, that returns n points randomly distributed on the true Pareto set.
`paretoFront`	[`function` \| NULL] Function, that returns n points randomly distributed on the true Pareto front.
`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).