Hello, My solver gives the variables to be optimized the minimum values to reach the objective while my objective function is a maximum (briefly the problem checks for each vehicles the location containing the maximum acquaintances and chose it then compares the chosen location with the real one in the database, where the strength of the social tie varies with time t. the variables controlling this variation are the ones to be optimised ) the relation variable r is calculated as followed where fr,fa,co are the ones to be optimized. friends,family and coworker are read in and the are values in [0,1]
i am using the following set of constrains to manage the maximum where m is the maximum and z3 is a binary where r in[0,100]:
i am using the following constrains to manage if(r=m)c1=1 else c1 =0, where z1,z2 are binaries r in[0,100] and m is the maximum.
to manage that if(m=0)c2=0 (with this i mean if r = m c should be 1 however if m =r=0, c should be zero)
to manage the conjunction of c1 and c 2
to manage that i have only one chosen location c per vehicle v i added (knowing that more than one r(v,e,t)can have a value equals to the maximum, removing this constraint did not improve anything):
my objective function is to maximize the following (the chosen edges e matching the ones in the database):
the variable to optimize are in the calculation of r(v,e,t)values. many thanks
asked
nardinebasta |

I cannot find a question in your exposition.

my question is how to possibly force the optimizer to maximize the values given to the variables to be optimized rather then the minimum values.

thank you