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Discussions and Closures
Discussion of “Application of the Firefly
Algorithm to Optimal Operation of Reservoirs
with the Purpose of Irrigation Supply
and Hydropower Production” by
Irene Garousi-Nejad, Omid Bozorg-Haddad,
Hugo A. Loáiciga, and Miguel A. Mariño
Downloaded from by on 10/27/17. Copyright ASCE. For personal use only; all rights reserved.
DOI: 10.1061/(ASCE)IR.1943-4774.0001064
Reza Ghasemzade 1
Ph.D. Student, Dept. of Environmental Engineering, Faculty of
Environment, Univ. of Tehran, 1417466191 Tehran, Iran. E-mail:
Among the vast range of evolutionary and metaheuristic optimization techniques that have been recently used in different fields of
water resources investigations, the firefly algorithm has not
been reported yet, although it has been thoroughly considered
and evaluated in the discussed paper.
In the discussed paper, the authors evaluated the performance of
the firefly algorithm (FA) for optimization of reservoir systems.
First, FA was applied to five mathematical test functions. Thereafter, the authors used FA to solve two reservoir operation problems
with different purposes, including irrigation supply and hydropower production. Their results demonstrated the superior performance of FA in terms of convergence rate to the global optima and
lower variance of results about global optima when compared with
a commonly used evolutionary algorithm, namely genetic algorithm (GA). Despite the great effort of the authors, the discusser
found several issues to add to the discussed subjects in the original
According to the mathematical test functions, although the authors attempted to cover different type of test functions, the authors
are questioned about not using any discrete problem to test FA. The
claim of “superior performance” cannot be approved until demonstrating an algorithm’s performance in discrete problems as well.
Another issue is that the authors did not consider the carryover
constraint for reservoir operation modeling. This constraint is
generally defined in reservoir operation modeling and can be found
in the papers by Garousi-Nejad and Bozorg-Haddad (2014),
Garousi-Nejad et al. (2016), and Bozorg-Haddad et al. (2015).
According to Eqs. (8) and (9) in the original paper, why did
the authors assume the tailwater (TR) to be constant? In fact,
this variable is a function of DisRet which is not a constant value.
This issue may affect the results.
According to Eq. (14) in the original paper and the descriptions
after this equation about Yang’s (2009) recommendation, why did
the authors use this formula? There are other formulations for this
purpose that could be used instead.
Even though the authors did a good job to mention different
types of penalty functions, namely additive and multiplicative, they
did not mention which type was used in their study. They have just
showed the formulations of the applied penalty functions through
Eqs. (17)–(19) and (23)–(25) in the original paper.
The main important issue is that why the authors used evolutionary and metaheuristic algorithms to solve reservoir operation
problems because the classic methods are less complicated, and
evolutionary or metaheuristic algorithms usually require more
processing time to find a solution. What makes the evolutionary
or metaheuristic algorithms appropriate for the purposes mentioned
in the original article?
The next issue is why the results of only five independent runs
were reported. As the authors of the original paper mentioned, the
number of runs taken in other articles were 15, 25, and even 100. Is
there any specific reason that just five runs were conducted or was
there a limitation forcing this number of runs?
Moreover, the authors used a number of functional evaluations
to compare the results of GA and FA without mentioning the reason
for using this criterion instead of number of iterations. Another important issue is that how the number of functional evaluations was
computed for each algorithm. When using the number of functional
evaluations to compare the performance of different algorithms, it
should be mentioned how they were computed.
Bozorg-Haddad, O., Moravej, M., and Loáiciga, H. (2015). “Application of
the water cycle algorithm to the optimal operation of reservoir systems.”
J. Irrig. Drain. Eng., 141(5), 10.1061/(ASCE)IR.1943-4774.0000832,
Garousi-Nejad, I., and Bozorg-Haddad, O. (2014). “The implementation of
developed firefly algorithm in multireservoir optimization in continuous
domain.” Int. J. Civ. Struct. Eng., 2(1), 104–108.
Garousi-Nejad, I., Bozorg-Haddad, O., and Loáiciga, H. (2016). “Modified
firefly algorithm for solving multireservoir operation in continuous and
discrete domains.” J. Water Resour. Plann. Manage., 10.1061/(ASCE)
WR.1943-5452.0000644, 04016029.
Yang, X. S. (2009). “Firefly algorithm for multimodal optimization.”
Stochastic Algorithms, 5792(2), 169–178.
J. Irrig. Drain Eng., 2018, 144(1): 07017018
J. Irrig. Drain. Eng.
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