Name
Abstract | ||
|---|---|---|
Artificial Bee Colony (ABC) Algorithm was firstly proposed for unconstrained optimization problems. Later many constraint processing techniques have been developed for ABC algorithms. According to the no free lunch theorem, it is impossible for a single constraint technique to be better than any other constraint technique on every issue. In this paper, artificial bee colony (ABC) algorithm with ensemble of constraint handling techniques (ECHT-ABC) is proposed to solve the constraint optimization problems. The performance of ECHT-ABC has been tested on 28 benchmark test functions for CEC 2017 Competition on Constrained Real-Parameter Optimization. The experimental results demonstrate that ECHT-ABC obtains very competitive performance compared with other state-of-the-art methods for constrained evolutionary optimization. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-319-95930-6_81 | INTELLIGENT COMPUTING THEORIES AND APPLICATION, PT I |
Keywords | Field | DocType |
Artificial Bee Colony (ABC) algorithm, Ensemble The constraint handling techniques | Constraint optimization problem,Artificial bee colony algorithm,Mathematical optimization,No free lunch theorem,Computer science,Constraint processing,Artificial intelligence,Optimization problem,Machine learning | Conference |
Volume | ISSN | Citations |
10954 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 14 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuehong Sun | 1 | 1 | 1.36 |
| Dan Wang | 2 | 101 | 40.29 |
| Jian-Xiang Wei | 3 | 1 | 0.68 |
| Ye Jin | 4 | 25 | 10.69 |
| Xin Xu | 5 | 162 | 40.08 |
| Ke-Lian Xiao | 6 | 0 | 0.34 |