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The results confirm the better performance of the HS algorithm to find the global optimal solution of this complex optimization problem, compared to the GA.
Practical procedures for designing optimal PI parameters and a feasible constraint set exclusive of complex optimization steps are also proposed.
The complex optimization problem that raised is mathematically formulated and solved by two algorithms.
Unfortunately, the efficiency of reasoners is usually obtained by implementing complex optimization techniques.
Moreover, fast computational algorithms to solve these more complex optimization problems are presented in [20].
In this paper, the complex optimization problem is solved with the IBM ILOG CPLEX Optimizer.
This simultaneous optimization problem was defined as an extremely complex optimization problem [18].
A genetic algorithm is especially suited for solving complex optimization problems.
To prove this, a case study characterized by a complex optimization scenario has been selected.
The proposed method requires neither complex optimization nor complex parameter adjustments.
But it is likely to be entrapped in a local extremum for some complex optimization problems.
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