Solving unconstrained binary quadratic programming using binary particle swarm optimization

被引：0
作者：
Lin, Geng [1 ]
机构：
[1] Minjiang Univ, Dept Math, Fuzhou, Peoples R China
来源：
INFORMATION TECHNOLOGY AND INDUSTRIAL ENGINEERING, VOLS 1 & 2 | 2014年
关键词：
unconstrained binary quadratic programming; binary particle swarm optimization; heuristic;
D O I：
10.2495/ITIE20130311
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The unconstrained binary quadratic programming is known to be NP-hard, and is a unified model for a lot of combinatorial optimization problems. This paper presents a binary particle swarm optimization for solving the unconstrained binary quadratic programming. The proposed algorithm adopts a method to update position, and uses mutation operation to produce new solutions. Then, the new solutions are refined by a local search procedure. The algorithm was tested on a benchmark set from the literature. The experimental results show that the proposed algorithm is able to find high-quality solutions within an acceptable runtime.
引用
收藏
页码：235 / 240
页数：6
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