caa a22 4500 605469040 CHVBK 20210128100320.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s00500-014-1371-0 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1371-0 A new approach to minimum attribute reduction based on discrete artificial bee colony [Elektronische Daten] [Dongyi Ye, Zhaojiong Chen] The minimum attribute reduction problem in the context of rough set theory is an NP-hard nonlinearly constrained combinatorial optimization problem. In this paper, we propose an efficient and competitive combinatorial artificial bee colony algorithm for solving the minimum attribute reduction problem. In the proposed algorithm, a new multidimensional binary local search scheme for bee colonies based on velocity computation is presented; an employed bee and its recruited onlooker bees use different local search strategies so as to get a possibly more diversified neighboring search around a current food source; the information of the so-far best solution is exploited in various ways by employed bees, onlookers and scouts, respectively; the monotonicity property of classification quality of attribute subsets from the theory of rough sets is employed to avoid possibly invalid local searches. Performance comparisons with some best performing population-based metaheuristic algorithms for the minimum attribute reduction problem were carried out on a number of UCI data sets. The experimental results show that the proposed algorithm overall outperforms all the other algorithms in terms of solution quality and is therefore promising for solving the minimum attribute reduction problem. Springer-Verlag Berlin Heidelberg, 2014 Minimum attribute reduction nationallicence Combinatorial artificial bee colony algorithm nationallicence Rough set nationallicence Ye Dongyi College of Mathematics and Computer Science, Fuzhou University, Fuzhou, People's Republic of China aut Chen Zhaojiong College of Mathematics and Computer Science, Fuzhou University, Fuzhou, People's Republic of China aut Soft Computing Springer Berlin Heidelberg 19/7(2015-07-01), 1893-1903 1432-7643 19:7<1893 2015 19 500 https://doi.org/10.1007/s00500-014-1371-0 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/s00500-014-1371-0 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Ye Dongyi College of Mathematics and Computer Science, Fuzhou University, Fuzhou, People's Republic of China aut NATIONALLICENCE 700 1- Chen Zhaojiong College of Mathematics and Computer Science, Fuzhou University, Fuzhou, People's Republic of China aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/7(2015-07-01), 1893-1903 1432-7643 19:7<1893 2015 19 500