.png){kind=icon}
返回
Similarity and Logic Gate-Based Tree-Seed Algorithms for Binary Optimization
.png){kind=icon}
PRE
AI
DOI：10.1016/j.cie.2017.12.009.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper focuses on solving binary optimization problems by using Tree-Seed Algorithm, TSA for short. While TSA is firstly proposed for solving optimization problems with continuously-structured solution space, TSA is modified to solve binary optimization problems, which is a subfield of discrete optimization, by using logic gates (LogicTSA) and similarity measurement techniques (SimTSA). In order to improve performance of these methods, a hybrid variant (SimLogicTSA) is also proposed. The performance of the proposed algorithms is investigated on uncapacitated facility location problems (UFLPs), which are pure binary optimization problems. The experimental results on 15 test instances are compared with each other and state-of-art algorithms. The comparisons demonstrate that hybrid variant of the algorithm is better than the other variants of the algorithm and state-of-art algorithms in terms of solution quality and robustness.
Keyword:
Binary optimization
Tree-seed algorithm
Similarity
Logic gate
Location analysis
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.5
论文数:
1.0W
被引数:
3.8W
机构
引用论文
.png){kind=icon}
Neighborhood search heuristics for the uncapacitated facility location problem无能力设施选址问题的邻域搜索启发式方法
PREAI
分享收藏
查看更多内容