Question: NLPSolve in Optimization - Got Warning

Dear Experts,

I got a warning with this sheet. I did a calculation in MathCAD11 without a warning - but with Levenberg-MArquardt. This method is missing in Maple12. How can I solve this fitting problem with Maple12 without a warning? Thanks in advanced.

> with(Optimization); datax := [10, 15, 20, 25, 30, 45, 60, 90, 120, 150, 180]; datay := [428, 334.1, 280.7, 262.7, 242.4, 212.9, 182.2, 151, 130.5, 116.9, 109.5]; tau := 1;
  [ImportMPS, Interactive, LPSolve, LSSolve, Maximize, Minimize, NLPSolve,

    QPSolve]
> model := N1*exp(lambda1*(t-tau))+N2*exp(lambda2*(t-tau));
              N1 exp(lambda1 (t - 1)) + N2 exp(lambda2 (t - 1))


> residuals := [sum((datay[i]-(eval(model, t = datax[i])))^2, i = 1 .. nops(datax))];
         [                                             2
         [(428 - N1 exp(9 lambda1) - N2 exp(9 lambda2))

                                                               2
            + (334.1 - N1 exp(14 lambda1) - N2 exp(14 lambda2))

                                                               2
            + (280.7 - N1 exp(19 lambda1) - N2 exp(19 lambda2))

                                                               2
            + (262.7 - N1 exp(24 lambda1) - N2 exp(24 lambda2))

                                                               2
            + (242.4 - N1 exp(29 lambda1) - N2 exp(29 lambda2))

                                                               2
            + (212.9 - N1 exp(44 lambda1) - N2 exp(44 lambda2))

                                                               2
            + (182.2 - N1 exp(59 lambda1) - N2 exp(59 lambda2))

                                                             2
            + (151 - N1 exp(89 lambda1) - N2 exp(89 lambda2))

                                                                 2
            + (130.5 - N1 exp(119 lambda1) - N2 exp(119 lambda2))

                                                                 2
            + (116.9 - N1 exp(149 lambda1) - N2 exp(149 lambda2))

                                                                 2]
            + (109.5 - N1 exp(179 lambda1) - N2 exp(179 lambda2)) ]


> NLPSolve((428-N1*exp(9*lambda1)-N2*exp(9*lambda2))^2+(334.1-N1*exp(14*lambda1)-N2*exp(14*lambda2))^2+(280.7-N1*exp(19*lambda1)-N2*exp(19*lambda2))^2+(262.7-N1*exp(24*lambda1)-N2*exp(24*lambda2))^2+(242.4-N1*exp(29*lambda1)-N2*exp(29*lambda2))^2+(212.9-N1*exp(44*lambda1)-N2*exp(44*lambda2))^2+(182.2-N1*exp(59*lambda1)-N2*exp(59*lambda2))^2+(151-N1*exp(89*lambda1)-N2*exp(89*lambda2))^2+(130.5-N1*exp(119*lambda1)-N2*exp(119*lambda2))^2+(116.9-N1*exp(149*lambda1)-N2*exp(149*lambda2))^2+(109.5-N1*exp(179*lambda1)-N2*exp(179*lambda2))^2, initialpoint = {N1 = 1.122*10^3, N2 = 1.2830*10^3, lambda1 = -0.39e-1, lambda2 = -.326}, method = nonlinearsimplex, evaluationlimit = 200000);
Warning, limiting number of function evaluations reached
  [Float(undefined), [N1 = 1121.15664672851563, N2 = 1281.37539672851564,

    lambda1 = Float(undefined), lambda2 = -0.253795410156250067]]
>