Open AccessA hybrid artificial bee colony algorithm for balancing two-sided assembly line with assignment constraints
Author(s) -
Jing Xiong,
Xiaokun Duan,
Erhua Wang
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1303/1/012145
Subject(s) - benchmark (surveying) , computer science , exploit , algorithm , artificial bee colony algorithm , set (abstract data type) , assembly line , process (computing) , scheme (mathematics) , mathematical optimization , artificial intelligence , mathematics , engineering , mechanical engineering , mathematical analysis , computer security , geodesy , programming language , geography , operating system
Two-sided assembly line balancing problem (TALBP) is a vital design problem for the industries. In real production process, some complex constraints should be considered in the two-sided assembly line. To solve the practical TALBP, this paper proposes a hybrid algorithm (HABC) that combines the artificial bee colony (ABC) algorithm and late acceptance hill-climbing (LAHC) algorithm. In the proposed algorithm, a well-designed decoding scheme is embedded to tackle multiple assignment constraints. Moreover, two neighborhood search strategies are implemented by employed bee and onlooker bee to explore and exploit the new solution. A set of computational experiments is performed on benchmark problems. The comparison results, best solutions, standard deviation and relative percentage index demonstrate that the HABC algorithm outperforms other algorithms published in the literature and finds 5 brand new solutions for 15 instances.