Migration Model of Adaptive Differential Evolution Applied to Real-World Problems

被引：3
作者：
Bujok, Petr [1 ]
机构：
[1] Univ Ostrava, Dept Informat & Comp, 30 Dubna 22, Ostrava 70103, Czech Republic
来源：
ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, ICAISC 2018, PT I | 2018年 / 10841卷
关键词：
Differential evolution; Migration model; Migration frequency; Sub-population size; Experimental study; Real-world problems; ALGORITHM; OPTIMIZATION; PARAMETERS;
D O I：
10.1007/978-3-319-91253-0_30
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Ten variants of migration model are compared with six adaptive differential evolution (DE) algorithms on real-world problems. Two parameters of migration model are studied experimentally. The results of experiments demonstrate the superiority of the migration models in first stages of the search process. A success of adaptive DE algorithms employed by migration model is systematically influenced by the studied parameters. The most efficient algorithm in the comparison is proposed migration model P15x50. The worst performing algorithm is adaptive DE.
引用
收藏
页码：313 / 322
页数：10
相关论文
共 18 条
[1]   Self-adapting control parameters in differential evolution: A comparative study on numerical benchmark problems [J].
Brest, Janez ;
Greiner, Saso ;
Boskovic, Borko ;
Mernik, Marjan ;
Zumer, Vijern .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2006, 10 (06) :646-657
[2]  
Bujok P., 2015, Acta Electrotech Info, V15, P49, DOI [10.15546/aeei-2015-0018, DOI 10.15546/AEEI-2015-0018]
[3]   Hierarchical Topology in Parallel Differential Evolution [J].
Bujok, Petr .
NUMERICAL METHODS AND APPLICATIONS (NMA 2014), 2015, 8962 :62-69
[4]   SYNCHRONOUS AND ASYNCHRONOUS MIGRATION IN ADAPTIVE DIFFERENTIAL EVOLUTION ALGORITHMS [J].
Bujok, Petr .
NEURAL NETWORK WORLD, 2013, 23 (01) :17-30
[5]  
Bujok P, 2012, LECT NOTES COMPUT SC, V7269, P39, DOI 10.1007/978-3-642-29353-5_5
[6]   Recent advances in differential evolution - An updated survey [J].
Das, Swagatam ;
Mullick, Sankha Subhra ;
Suganthan, P. N. .
SWARM AND EVOLUTIONARY COMPUTATION, 2016, 27 :1-30
[7]   Differential Evolution: A Survey of the State-of-the-Art [J].
Das, Swagatam ;
Suganthan, Ponnuthurai Nagaratnam .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2011, 15 (01) :4-31
[8]   Parallel Self-Adaptive Differential Evolution Algorithm for Solving Short-Term Hydro Scheduling Problem [J].
Glotic, Arnel ;
Glotic, Adnan ;
Kitak, Peter ;
Pihler, Joze ;
Ticar, Igor .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2014, 29 (05) :2347-2358
[9]   Distributed evolutionary algorithms and their models: A survey of the state-of-the-art [J].
Gong, Yue-Jiao ;
Chen, Wei-Neng ;
Zhan, Zhi-Hui ;
Zhang, Jun ;
Li, Yun ;
Zhang, Qingfu ;
Li, Jing-Jing .
APPLIED SOFT COMPUTING, 2015, 34 :286-300
[10]   Differential evolution algorithm with ensemble of parameters and mutation strategies [J].
Mallipeddi, R. ;
Suganthan, P. N. ;
Pan, Q. K. ;
Tasgetiren, M. F. .
APPLIED SOFT COMPUTING, 2011, 11 (02) :1679-1696
12