# Copyright 2013, Gurobi Optimization, Inc. # # This example formulates and solves the following simple QCP model: # minimize # x^2 + x*y + y^2 + y*z + z^2 # subject to # x + 2 y + 3z >= 4 # x + y >= 1 # t = 0.7071 # [ x ^ 2 + y ^ 2 - t ^ 2 ] < = 0 (a second-order cone constraint) library("gurobi") model <- list() model$A <- matrix(c(1,2,3,0,1,1,0,0,0,0,0,1), nrow=3, byrow=T) model$Q <- matrix(c(2,1,0,0,1,2,1,0,0,1,2,0,0,0,0,0), nrow=4, byrow=T) model$cones <- list(list(4,1,2)) model$obj <- c(1,2,3,0) model$rhs <- c(4,1,0.717067811) model$sense <- c('>=', '>=', '=') result <- gurobi(model) print(result$objval) print(result$x)