I am trying to use NMinimize to minimize a real-valued function of complex arguments, with a supplied initial point. This doesn't seem to work well. For example, the following gives errors like "LessEqual: invalid comparison":

NMinimize[Re[x*y], {x, y}, Method -> {"SimulatedAnnealing", "InitialPoints" -> {{1 + I, 1 - I}}}]

Of course I could redescribe my function in terms of 4 real variables, the real and imaginary parts of x and y respectively. When I do this everything works fine. But it is a big hassle (the actual complex function I want to optimize is nontrivial.) Furthermore I feel that this is such a trivial translation NMinimize should be capable of doing it under the hood.

So my question is as follows: what is the easiest way to use NMinimize to minimize a real-valued function of complex variables, so that it can handle an initial point.


1 Answer 1


Searching through the documentation for NMinimize, there is no mention of complex numbers. However, you can simply write your own complexNMinimize which appropriately handles the transformations of variables: x -> x$Re + I x$Im.

complexNMinimize[cf_, cVars_, cIniPnts_] := 
 Module[{f, vars, iniPnts, res},
  vars = {# -> 
        Symbol[SymbolName[#] <> "$Re"] + 
     I Symbol[SymbolName[#] <> "$Im"]} & /@ cVars // Flatten;
  f = cf /. vars;
  iniPnts = ReIm /@ cIniPnts // Flatten;

  res = NMinimize[f, Variables@*Last /@ vars // Flatten, 
    Method -> {"SimulatedAnnealing", "InitialPoints" -> {iniPnts}}];

  {First@res, vars /. Last@res}

f = Abs[x - 2 + I] + Abs[y + 3 - 2 I];
complexNMinimize[f, {x, y}, {1 + I, 1 - I}]
(* {3.79948*10^-8, {x -> 2. - 1. I, y -> -3. + 2. I}} *)

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