caa a22 4500 606159258 CHVBK 20210128100623.0 cr unu---uuuuu 210128e20151001xx s 000 0 eng 10.1007/s00521-015-1826-y doi (NATIONALLICENCE)springer-10.1007/s00521-015-1826-y Brajevic Ivona Faculty of Mathematics, University of Belgrade, Studentski trg 16, 11000, Belgrade, Serbia aut Crossover-based artificial bee colony algorithm for constrained optimization problems [Elektronische Daten] [Ivona Brajevic] Artificial bee colony (ABC) algorithm represents one of the most-studied swarm intelligence algorithms. Since the original ABC has been found to be very effective, today there are a lot of improved variants of ABC algorithm used to solve a wide range of hard optimization problems. This paper describes a novel artificial bee colony algorithm for constrained optimization problems. In the proposed algorithm, five modifications are introduced. Firstly, to improve the exploitation abilities of ABC, two different modified ABC search operators are used in employed and onlooker phases, and crossover operator is used in scout phase instead of random search. Secondly, modifications related to dynamic tolerance for handling equality constraints and improved boundary constraint-handling method are employed. The experimental results, obtained by testing on a set of 24 well-known benchmark functions and four widely used engineering design problems, show that the proposed approach can outperform ABC-based approaches for constrained optimization problems in terms of the quality of the results, robustness and convergence speed. Additionally, it provides better results in most cases compared with other state-of-the-art algorithms. The Natural Computing Applications Forum, 2015 Artificial bee colony algorithm nationallicence Constrained optimization nationallicence Nature-inspired algorithms nationallicence Swarm intelligence nationallicence Exploitation nationallicence Exploration nationallicence Neural Computing and Applications Springer London 26/7(2015-10-01), 1587-1601 0941-0643 26:7<1587 2015 26 521 https://doi.org/10.1007/s00521-015-1826-y text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-015-1826-y text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Brajevic Ivona Faculty of Mathematics, University of Belgrade, Studentski trg 16, 11000, Belgrade, Serbia aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/7(2015-10-01), 1587-1601 0941-0643 26:7<1587 2015 26 521