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عنوان انگلیسی مقاله:
FBI inspired meta-optimization
ترجمه فارسی عنوان مقاله:
اف بی آی الهام گرفته از متا بهینه سازی
Sciencedirect - Elsevier - Applied Soft Computing Journal, 93 (2020) 106339. doi:10.1016/j.asoc.2020.106339
Jui-Sheng Chou ∗, Ngoc-Mai Nguyen
This study developed a novel optimization algorithm, called Forensic-Based Investigation (FBI), inspired
by the suspect investigation–location–pursuit process that is used by police officers. Although
numerous unwieldy optimization algorithms hamper their usability by requiring predefined operating
parameters, FBI is a user-friendly algorithm that does not require predefined operating parameters.
The performance of parameter-free FBI was validated using four experiments: (1) The robustness and
efficiency of FBI were compared with those of 12 representations of the top leading metaphors by
using 50 renowned multidimensional benchmark problems. The result indicated that FBI remarkably
outperformed all other algorithms. (2) FBI was applied to solve a resource-constrained scheduling
problem associated with a highway construction project. The experiment demonstrated that FBI
yielded the shortest schedule with a success rate of 100%, indicating its stability and robustness.
(3) FBI was utilized to solve 30 benchmark functions that were most recently presented at the
IEEE Congress on Evolutionary Computation (CEC) competition on bound-constrained problems. Its
performance was compared with those of the three winners in CEC to validate its effectiveness.
(4) FBI solved high-dimensional problems, by increasing the number of dimensions of benchmark
functions to 1000. FBI is efficient because it requires a relatively short computational time for solving
problems, it reaches the optimal solution more rapidly than other algorithms, and it efficaciously solves
high-dimensional problems. Given that the experiments demonstrated FBI’s robustness, efficiency,
stability, and user-friendliness, FBI is promising for solving various complex problems. Finally, this
study provided the scientific community with a metaheuristic optimization platform for graphically
and logically manipulating optimization algorithms.
Keywords: Forensic-based investigation algorithm | Metaheuristic optimization | Swarm intelligence and evolutionary | computation | Benchmark functions | Construction engineering and project | management