search for: fmincon

Dear all R users, I am wondering if there are any function for Constraint optimization in R. Especially i am looking for a R - equivalent of "fmincon" function in MATLAB. Thanks and regards, Arun [[alternative HTML version deleted]]

...inear (obj funct) with linear constraints.I know about the "ms" and "nls" functions, but these seem only for nonlinear regression, not nonlinear minimization. I am looking for a pure non-linear optimization module. The nonlinear optimization functions I used in MatLab are "fmincon" and "fminunc" Is there any nonlinear optimization algorithm for R? Thanks. Rob

...); objFunc_vol(C); objFunc = @(C) compute_strategy_before_fees(prices, C, floor, cap, m_ret_reb, prices_TR, hedge_fund, vg, euribor, last_reb_date, Maturity, fixed_fees, var_fees); objFunc(C); options = optimset('MaxIter',10000000,'MaxFunEvals',10000000); tic; % OPTIMISE %M = fmincon(objFunc,C,[],[],[],[],repmat(-20,12,9),repmat(20,12,9), at TriskellConstraints,options); M = fmincon(objFunc_vol,C,[],[],[],[],repmat(-20,12,9),repmat(20,12,9), at TriskellConstraints,options); [Z, ZZ] = compute_strategy_after_fees(prices, C, floor, cap, m_ret_reb, prices_TR, Hedge_Fund, vg, euribo...

...doch <murdoch.duncan at gmail.com> wrote: > I haven't run your code, but since Kendall correlation is based on > ranks, your Fn is probably locally constant with jumps when the ranks > change. That's a really hard kind of function to maximize, and the > algorithm used by fmincon is not appropriate to do it. > > Sorry, but I don't know if there is an R function that can do > constrained discrete maximization. > > Duncan Murdoch > > On 2025-03-27 2:35 p.m., Daniel Lobo wrote: > > Hi, > > > > I have below minimization problem > &g...

...ss a huge data set to a function. Is there any situations that R doesn't copy the data, besides pass data in an environment object. 2) Does R pre-compile the object function to binary when running "optim"? I experienced the R "optim" is much slower than the MATLAB "fmincon" function. I don't know MATLAB has done any pre-compilation on the script for object function or not. But perhaps, we can increase R performance by some sort of pre-compilation during running time. Thanks in advance. Best Regards, Ruihong

I haven't run your code, but since Kendall correlation is based on ranks, your Fn is probably locally constant with jumps when the ranks change. That's a really hard kind of function to maximize, and the algorithm used by fmincon is not appropriate to do it. Sorry, but I don't know if there is an R function that can do constrained discrete maximization. Duncan Murdoch On 2025-03-27 2:35 p.m., Daniel Lobo wrote: > Hi, > > I have below minimization problem > > > MyDat = structure(list(c(50L, 0L, 0...

...r a R-function that performs nonlinear constraint optimization (where the objective function and the constraints are allowed to be nonlinear). More specifically, I am trying to figure out whether there is an equivalent function of NAG fortran library' "E04UCF" or matlab's "fmincon" in R. Any help is greatly appreciated. Thank you, Sunduz PS: fmincon is described at http://www.mathworks.com/access/helpdesk/help/toolbox/optim/optim.shtml?BB=1

...5L, 100L, 85L, 85L, 85L, 0L, 85L, 85L, 85L, 85L, 85L, 85L, 85L, 85L, 28L, 56L, 56L)), row.names = c(NA, -30L), class = "data.frame") Fn = function(Wts) return(-Kendall::Kendall(1:Nobs, rank(-as.vector(as.matrix(MyDat) %*% matrix(Wts, nc = 1)[, 1, drop = T])))$tau[1]) q1 = pracma::fmincon(c(0.12, 0.04, 0.07, 0.03, 0.06, 0.07, 0.07, 0.04, 0.09, 0.08, 0.02, 0.02, 0.03, 0.06, 0.02, 0, 0.07, 0.05, 0.02, 0.02, 0.02), fn = Fn, A = matrix(c(rep(0, 20), -1), nrow = 1), b = -2.05/100, Aeq = matrix(c(rep(1, 20), 1), nrow = 1), beq = 1, lb = rep(0.01, 21), tol = 1...

...L, 85L, 85L, 85L, 85L, 85L, > 85L, 28L, 56L, 56L)), row.names = c(NA, -30L), class = "data.frame") > > Fn = function(Wts) return(-Kendall::Kendall(1:dim(MyDat)[1], > rank(-as.vector(as.matrix(MyDat) %*% matrix(Wts, nc = 1)[, 1, drop = > T])))$tau[1]) > q1 = pracma::fmincon(c(0.12, 0.04, 0.07, 0.03, 0.06, 0.07, 0.07, 0.04, > 0.09, 0.08, 0.02, 0.02, 0.03, 0.06, 0.02, 0, 0.07, 0.05, 0.02, 0.02, 0.02), > fn = Fn, > A = matrix(c(rep(0, 20), -1), nrow = 1), b = -2.05/100, Aeq = > matrix(c(rep(1, 20), 1), nrow = 1), beq = 1, > lb = rep(0...

...00L, 85L, 85L, 85L, 0L, 85L, 85L, 85L, 85L, 85L, 85L, 85L, 85L, 28L, 56L, 56L)), row.names = c(NA, -30L), class = "data.frame") Fn = function(Wts) return(-Kendall::Kendall(1:dim(MyDat)[1], rank(-as.vector(as.matrix(MyDat) %*% matrix(Wts, nc = 1)[, 1, drop = T])))$tau[1]) q1 = pracma::fmincon(c(0.12, 0.04, 0.07, 0.03, 0.06, 0.07, 0.07, 0.04, 0.09, 0.08, 0.02, 0.02, 0.03, 0.06, 0.02, 0, 0.07, 0.05, 0.02, 0.02, 0.02), fn = Fn, A = matrix(c(rep(0, 20), -1), nrow = 1), b = -2.05/100, Aeq = matrix(c(rep(1, 20), 1), nrow = 1), beq = 1, lb = rep(0.01, 21), tol = 1...

...gmail.com> > wrote: > >> I haven't run your code, but since Kendall correlation is based on >> ranks, your Fn is probably locally constant with jumps when the ranks >> change. That's a really hard kind of function to maximize, and the >> algorithm used by fmincon is not appropriate to do it. >> >> Sorry, but I don't know if there is an R function that can do >> constrained discrete maximization. >> >> Duncan Murdoch >> >> On 2025-03-27 2:35 p.m., Daniel Lobo wrote: >>> Hi, >>> >>> I ha...

..., 85L, 85L, 85L, 85L, 85L, 85L, 85L, > 85L, 28L, 56L, 56L)), row.names = c(NA, -30L), class = "data.frame") > > Fn = function(Wts) return(-Kendall::Kendall(1:Nobs, > rank(-as.vector(as.matrix(MyDat) %*% matrix(Wts, nc = 1)[, 1, drop = > T])))$tau[1]) > q1 = pracma::fmincon(c(0.12, 0.04, 0.07, 0.03, 0.06, 0.07, 0.07, 0.04, > 0.09, 0.08, 0.02, 0.02, 0.03, 0.06, 0.02, 0, 0.07, 0.05, 0.02, 0.02, 0.02), > fn = Fn, > A = matrix(c(rep(0, 20), -1), nrow = 1), b = -2.05/100, Aeq = > matrix(c(rep(1, 20), 1), nrow = 1), beq = 1, > lb = rep(0...

Hi, I need to solve an optimization problem in R having linear objective function and quadratic constraints(number of variables is around 80). What are the possible choices to do this in R. optim() function only allows box constrained problems. Is it possible in nlm()? Or please tell me if there is any other routine. Thanks Amit

...ss a huge data set to a function. Is there any situations that R doesn't copy the data, besides pass data in an environment object. 2) Does R pre-compile the object function to binary when running "optim"? I experienced the R "optim" is much slower than the MATLAB "fmincon" function. I don't know MATLAB has done any pre-compilation on the script for object function or not. But perhaps, we can increase R performance by some sort of pre-compilation during running time. Thanks in advance. Best Regards, Ruihong ------------------------------ Message: 87...