Iterated tabu search for the unconstrained binary quadratic optimization problem

被引：0
|
作者：
Palubeckis, Gintaras [1 ]
机构：
[1] Kaunas Univ Technol, Dept Pract Informat, LT-51368 Kaunas, Lithuania
来源：
INFORMATICA | 2006年 / 17卷 / 02期
关键词：
binary quadratic optimization; iterated tabu search; heuristics;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Given a set of objects with profits (any, even negative, numbers) assigned not only to separate objects but also to pairs of them, the unconstrained binary quadratic optimization problem consists in finding a subset of objects for which the overall profit is maximized. In this paper, an iterated tabu search algorithm for solving this problem is proposed. Computational results for problem instances of size up to 7000 variables (objects) are reported and comparisons with other up-to-date heuristic methods are provided.
引用
收藏
页码：279 / 296
页数：18
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