iteration_num: 1
solve_status: OPTIMAL
objective_value= -348008.5633985514
End No. 1iteration
iteration_num: 2
solve_status: OPTIMAL
objective_value= -347208.20356227603
End No. 2iteration
iteration_num: 3
solve_status: OPTIMAL
objective_value= -346579.9134321452
End No. 3iteration
iteration_num: 4
solve_status: OPTIMAL
objective_value= -346578.3008976437
End No. 4iteration
iteration_num: 5
solve_status: OPTIMAL
objective_value= -346574.3435993286
End No. 5iteration
iteration_num: 6
solve_status: OPTIMAL
objective_value= -346574.34265981923
End No. 6iteration
iteration_num: 7
solve_status: OPTIMAL
objective_value= -346574.25081370655
End No. 7iteration
iteration_num: 8
solve_status: OPTIMAL
objective_value= -346574.25081370474
End No. 8iteration
iteration_num: 9
solve_status: OPTIMAL
objective_value= -346574.25081370474
End No. 9iteration
iteration_num: 10
solve_status: OPTIMAL
objective_value= -346574.25081370474
End No. 10iteration
iteration_num: 11
solve_status: OPTIMAL
objective_value= -346574.25081370474
End No. 11iteration
iteration_num: 12
solve_status: OPTIMAL
objective_value= -346574.25081370474
End No. 12iteration
iteration_num: 13
solve_status: OPTIMAL
objective_value= -346574.25081370474
End No. 13iteration
iteration_num: 14
solve_status: OPTIMAL
objective_value= -346574.25081370474
End No. 14iteration
iteration_num: 15
solve_status: OPTIMAL
objective_value= -346574.25081370474
End No. 15iteration
END
