intfminbnd Solves a multi-variable optimization problem on a bounded interval xopt = intfminbnd(f,intcon,x1,x2) xopt = intfminbnd(f,intcon,x1,x2,options) [xopt,fopt] = intfminbnd(.....) [xopt,fopt,exitflag]= intfminbnd(.....) [xopt,fopt,exitflag,output]=intfminbnd(.....) [xopt,fopt,exitflag,gradient,hessian]=intfminbnd(.....) f : a function, representing the objective function of the problem x1 : a vector, containing the lower bound of the variables. x2 : a vector, containing the upper bound of the variables. intcon : a vector of integers, represents which variables are constrained to be integers options : a list, containing the option for user to specify. See below for details. xopt : a vector of doubles, containing the the computed solution of the optimization problem. fopt : a scalar of double, containing the the function value at x. exitflag : a scalar of integer, containing the flag which denotes the reason for termination of algorithm. See below for details. gradient : a vector of doubles, containing the Objective's gradient of the solution. hessian : a matrix of doubles, containing the Objective's hessian of the solution. Search the minimum of a multi-variable function on bounded interval specified by : Find the minimum of f(x) such that \begin{eqnarray} &\mbox{min}_{x} & f(x)\\ & \text{subject to} & x1 \ < x \ < x2 \\ \end{eqnarray} The routine calls Bonmin for solving the Bounded Optimization problem, Bonmin is a library written in C++. The options allows the user to set various parameters of the Optimization problem. It should be defined as type "list" and contains the following fields. Syntax : options= list("IntegerTolerance", [---], "MaxNodes",[---], "MaxIter", [---], "AllowableGap",[---] "CpuTime", [---],"gradobj", "off", "hessian", "off" ); IntegerTolerance : a Scalar, a number with that value of an integer is considered integer.. MaxNodes : a Scalar, containing the Maximum Number of Nodes that the solver should search. CpuTime : a Scalar, containing the Maximum amount of CPU Time that the solver should take. AllowableGap : a Scalar, to stop the tree search when the gap between the objective value of the best known solution is reached. MaxIter : a Scalar, containing the Maximum Number of Iteration that the solver should take. gradobj : a string, to turn on or off the user supplied objective gradient. hessian : a Scalar, to turn on or off the user supplied objective hessian. Default Values : options = list('integertolerance',1d-06,'maxnodes',2147483647,'cputime',1d10,'allowablegap',0,'maxiter',2147483647,'gradobj',"off",'hessian',"off") The exitflag allows to know the status of the optimization which is given back by Ipopt. exitflag=0 : Optimal Solution Found exitflag=1 : Maximum Number of Iterations Exceeded. Output may not be optimal. exitflag=2 : Maximum CPU Time exceeded. Output may not be optimal. exitflag=3 : Stop at Tiny Step. exitflag=4 : Solved To Acceptable Level. exitflag=5 : Converged to a point of local infeasibility. For more details on exitflag see the Bonmin documentation, go to http://www.coin-or.org/Bonmin Harpreet Singh