ON THE CLASSIFICATION OF HEURISTIC ALGORITHMS
EURISTINIŲ ALGORITMŲ KLASIFIKAVIMAS

Summary/Abstract: In this paper, the issues related to the classification (taxonomy) of heuristic optimization algorithms are discussed. Firstly, the main goals and features of heuristic techniques are introduced. Further, we outline some important classification schemes (templates) for the classical and modern heuristic algorithms such as (descent) local search, simulated annealing, tabu search, genetic (evolutionary) algorithms, ant colony optimization, etc. We also analyze the basic aspects of a universal classification template based on a set of so-called substantial concepts, i.e. the fundamental structural components of the algorithms. The paper is completed with concluding remarks.

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