使用 CPLEX/AMPL 解决的 SOCP 问题比使用 CPLEX/MATLAB 解决的速度快 10 倍，为什么？

Question

I solved an optimal power flow (OPF) problem modeled as a second-order cone programming (SOCP). At first I solved using solver CPLEX in AMPL lenguage, and took 0.08s; then I solved the same problem with CPLEX for Matlab (command cplexqcp) and took 0.86s. Times shown correspond only to the times demand by the solver (CPLEX). Does anyone know what makes such a time difference? Time results for CPLEX/AMPL:

Elapsed AMPL time :     0.430s
Elapsed Solve time :     0.080s
Elapsed CPU time:     0.510s 

Time results for CPLEX/MATLAB:

:
tic
[x,fval]=cplexqcp([],f,[],[],Aeq,beq,l,Qc,r,Li,Ls);
toc
:
Elapsed time is 0.860856 seconds.

Note: The problem has 542 variables.

Answer 1

Hard to say without access to the detail, but my first guess would be preprocessing. Before passing the problem to the solver, AMPL will attempt to simplify it eg eliminating variables that are dependent on other variables. This can make a significant difference to the solution time.

(For large problems, it can also make a big difference to data I/O time between AMPL and solver, but for only 542 variables that's probably not a big issue.)

Another possibility is that AMPL and Matlab are invoking CPLEX with different options (eg different solution tolerances).