International Journal on Advances in Systems and Measurements, vol 10 no 1 & 2, year 2017, http://www.iariajournals.org/systems_and_measurements/ 86 Comparative Analysis of Heuristic Algorithms for Solving Multiextremal Problems Rudolf Neydorf, Ivan Chernogorov, Victor Polyakh Dean Vucinic Orkhan Yarakhmedov, Yulia Goncharova Vesalius College Department of Software Computer Technology and Vrije Universiteit Brussel Automated Systems and Department of Scientific- Brussels, Belgium Technical Translation and Professional Communication Don State Technical University Email:
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[email protected] Abstract—In this paper, 3 of the most popular search Many modern practical optimization problems are optimization algorithms are applied to study the multi- inherently complicated by counterpoint criterion extremal problems, which are more extensive and complex requirements of the involved optimized object. The expected than the single-extremal problems. This study has shown that result - the global optimum - for the selected criteria is not only the heuristic algorithms can provide an effective solution always the best solution to consider, because it incorporate to solve the multiextremal problems. Among the large group of many additional criteria and restrictions. It is well known available algorithms, the 3 methods have demonstrated the that such situations arise in the design of complex best performance, which are: (1) particles swarming modelling technological systems when solving transportation and method, (2) evolutionary-genetic extrema selection and (3) logistics problems among many others. In addition, many search technique based on the ant colony method. The objects in their technical and informational nature are prone previous comparison study, where these approaches have been applied to an overall test environment with the multiextremal to multi-extreme property.