A comparison of several heuristic algorithms for solving high dimensional optimization problems (CROSBI ID 620832)
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Podaci o odgovornosti
Nyarko, Emmanuel Karlo ; Cupec, Robert ; Filko, Damir
engleski
A comparison of several heuristic algorithms for solving high dimensional optimization problems
The number of heuristic optimization algorithms has exploded over the last decade with new methods being proposed constantly. A recent overview of existing heuristic methods has listed over 130 algorithms. The majority of these optimization algorithms have been designed and applied to solve real-parameter function optimization problems, each claiming to be superior to other methods in terms of performance. In this paper, three heuristic algorithms are systematically analyzed and tested in detail for real-parameter optimization problems, especially those involving a large number of parameters. Three traditional methods, i.e., genetic algorithms (GA), particle swarm optimization (PSO) and differential evolution (DE) are compared in terms of accuracy and runtime, using several high dimensional standard benchmark functions and real world problems.
heuristic optimization; high dimensional optimization; optimization techniques; nature-inspired algorithms
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Podaci o prilogu
2014.
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objavljeno
Podaci o matičnoj publikaciji
Podaci o skupu
32nd Science in Practice 2014 (SiP 2014)
predavanje
15.10.2014-17.10.2014
Osijek, Hrvatska