New to Optimization & JuMP. Trying to do sensitivity analysis for this example, and wondering how to get reduced costs, objective coefficients, allowable increase/decrease, shadow prices, and final values for given constraints. They are very easy to get on excel solver. Read through the documentation here, http://www.juliaopt.org/JuMP.jl/v0.18/refexpr.html, but not helpful.
#Initialise values n=4;r=[.1;.15;.16; 0.08] A = [1 1 1 1] b = 80 D = [.5 .3 .25 .6; .3 .1 .4 .2; .2 .6 .35 .2] d = [28; 24; 12] using JuMP using Gurobi #Define Model model = Model(solver=GurobiSolver(Presolve=0)) #Define variables @variable(model, x[1:4]) #Define Objective @objective(model, Max, r'*x) #Define constraints @constraints model begin x .>= zeros(1,4) A*x .== b D*x .>= d end status = solve(model) getvalue(x) # Giving correct final values println(getdual(x)) # The duals are shown as zeros