what changes should i make in final optimised value with opt time vector

Yes, it is possible. The fval returned in both the problem-based and solver-based solvers can always be trusted to agree up to an additive constant. However, the problem-based framework allows you to specify a linear program objective function of the form f.'*x + f0, whereas the solver-based linear program solvers do not. If you feed a problem description structure to a solver-based solver, it will always ignore the f0 that you specify and assume f0=0. That is why there is a difference of 2.7 in the fvals in the example below.

x=optimvar('x',2,'LowerBound',0);
objective=dot(x,-[5,4])+2.7;
constraints.con1=sum(x)<=3;
constraints.con2=dot(x,[2,7])<=pi;
prob=optimproblem('Objective',objective,'Constraints',constraints);
%%%%% Problem based
[sol,fval1]=solve(prob);  
Solving problem using linprog.

Optimal solution found.
x1=sol.x,fval1
x1 = 2×1
    1.5708
         0
fval1 = -5.1540
%%%%%% Solver-based equivalent
s=prob2struct(prob);
[x2,fval2]=linprog(s) 
Optimal solution found.
x2 = 2×1
    1.5708
         0
fval2 = -7.8540
difference=fval1-fval2
difference = 2.7000

NN 2021-9-27

When i tried to use probstruct , it gives the following error

Unable to convert 'struct' to 'sym'.

Please advice

Matt J 2021-9-27

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what changes should i make in final optimised value with opt time vector

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what changes should i make in final optimised value with opt time vector

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