返回
Artificial bee colony algorithm using permutation encoding for the bounded diameter minimum spanning tree problem
DOI:10.1007/s00500-021-05913-z.png)
摘要
En 中文
The bounded diameter minimum spanning tree (BD-MST) problem seeks a spanning tree (T) of minimum weight on a given connected, undirected and edge-weighted graph subject to the diameter of T does not exceed D >= 2, where D is a given positive integer. The BD-MST problem isNP-hard problem and finds many real-world applications. In this paper, we propose an artificial bee colony (ABC) algorithm for the BD-MST problem. ABC algorithm is a swarm-based metaheuristic technique based on the intelligent foraging behavior of honeybees. The proposed ABC algorithm employs permutation encoding. To exploit this encoding structure, two neighborhood strategies that help ABC algorithm in faster convergence towards finding high quality solutions are applied. On a set of Euclidean and non-Euclidean benchmark instances for various diameter bounds, the proposed approach has been compared with state-of-the-art approaches. Computational results demonstrate the effectiveness of the proposed approach to the other extant approaches in the literature.
Keyword:
Spanning tree
Bounded-diameter
Swarm intelligence
Artificial bee colony algorithm
Permutation encoding
Neighborhood strategies
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:
2.5
论文数:
1.0W
被引数:
2.1W
机构
引用论文
Electrical properties of iron-silica nanocomposites synthesized by electrodeposition电沉积法制备的铁-二氧化硅纳米复合材料的电学性质
Serial and parallel memetic algorithms for the bounded diameter minimum spanning tree problem
EXPERT SYSTEMS
IF2.3
Use of a Regional Approach for Long-Term Simulation of Snow Avalanche Regime: a Case Study in the Italian Alps采用区域方法进行雪崩状况长期模拟:意大利阿尔卑斯山案例研究
Integration of proxy data and model scenarios for the mid-Holocene onset of modern ENSO variability代理数据与模型情景的整合:中全新世现代ENSO变率的起始

