.png){kind=icon}
返回
Hybrid teaching-learning-based optimization algorithms for the Quadratic Assignment Problem
.png){kind=icon}
PRE
AI
DOI：10.1016/j.cie.2015.03.001.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Teaching-Learning-Based Optimization (TLBO) is a novel swarm intelligence metaheuristic that is reported as an efficient solution method for many optimization problems. It consists of two phases where all individuals are trained by a teacher in the first phase and interact with classmates to improve their knowledge level in the second phase. In this study, we propose a set of TLBO-based hybrid algorithms to solve the challenging combinatorial optimization problem, Quadratic Assignment. Individuals are trained with recombination operators and later a Robust Tabu Search engine processes them. The performances of sequential and parallel TLBO-based hybrid algorithms are compared with those of state-of-the-art metaheuristics in terms of the best solution and computational effort. It is shown experimentally that the performance of the proposed algorithms are competitive with the best reported algorithms for the solution of the Quadratic Assignment Problem with which many real life problems can be modeled. (C) 2015 Elsevier Ltd. All rights reserved.
Keyword:
Teaching-learning
Hybrid algorithm
Robust tabu
Quadratic assignment
Stagnation
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
暂无机构信息
引用论文
Kinematic and kinetic differences in the execution of vertical jumps between people with good and poor ankle joint dorsiflexion踝关节背屈良好和不良的人在执行垂直跳跃时的运动学和动力学差异
PREAI
分享收藏
A Three-Lesson Teaching Unit Significantly Increases High School Students’ Knowledge about Epilepsy and Positively Influences Their Attitude towards This Disease.png)
PLOS ONE
OAAI
PLOS ONEIF0
OAAI分享收藏Risks of treated anxiety, depression, and insomnia among nurses: A nationwide longitudinal cohort studyPLOS ONEOAAI
PLOS ONEIF0
OAAI分享收藏
查看更多内容