Research on Neighborhood Search Strategy of Artificial Bee Colony Algorithm for Satisfiability Problems

被引：2
|
作者：
Guo, Ying [1 ]
Zhang, Changsheng [2 ]
机构：
[1] Ningxia Inst Technol, Coll Elect & Informat Engn, Shizuishan, Peoples R China
[2] Northeastern Univ, Sch Comp Sci & Engn, Shenyang, Peoples R China
来源：
2017 10TH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID), VOL. 1 | 2017年
关键词：
artificial bee colony algorithm; satisfiability problems; neighborhood selection; new solution generation; OPTIMIZATION;
D O I：
10.1109/ISCID.2017.171
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The neighborhood search process plays an important role in artificial bee colony algorithm. Aiming at the problems caused by ignoring the characteristics of a given problem, the neighborhood search strategy for satisfiability problems is studied. To balance the ability of global exploration and local search, the BIR and RIB neighborhood selection strategies are proposed, and four new solution generation strategies are compared and studied. The experimental results show that, compared with the original method, the proposed strategies have improved in varying degrees in performance for stochastic SAT problems.
引用
收藏
页码：123 / 126
页数：4
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