Enhanced heuristic approach for Traveling Tournament Problem based on Grey Wolf Optimizer

D. Gupta, Chand Anand, Tejas Dewan
{"title":"Enhanced heuristic approach for Traveling Tournament Problem based on Grey Wolf Optimizer","authors":"D. Gupta, Chand Anand, Tejas Dewan","doi":"10.1109/IC3.2015.7346685","DOIUrl":null,"url":null,"abstract":"This paper shows an enhanced heuristic approach of grey wolf optimizer and simulated annealing in order to find optimum solution for Travelling Tournament Problem. In this paper, we tackle the mirrored version of TTP. We use a fast constructive heuristic algorithm to generate schedules. Later we integrate an enhanced heuristic approach of simulated annealing based on prey proximity model of Grey Wolf Optimizer to obtain least cost tournament schedule. We upgrade the position updating step of GWO by using probabilistic methods and hybridize it with SA to solve TTP and avoid getting stuck in local minima. Our proposed hybrid algorithm converges to an optimum solution for TTP. We calculate the overall cost of TTP and compare the performance of our alorithm with other metaheuristic algorithms like MBBO/ESA, BBO/SA, ACO and PSO.","PeriodicalId":217950,"journal":{"name":"2015 Eighth International Conference on Contemporary Computing (IC3)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Eighth International Conference on Contemporary Computing (IC3)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC3.2015.7346685","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

This paper shows an enhanced heuristic approach of grey wolf optimizer and simulated annealing in order to find optimum solution for Travelling Tournament Problem. In this paper, we tackle the mirrored version of TTP. We use a fast constructive heuristic algorithm to generate schedules. Later we integrate an enhanced heuristic approach of simulated annealing based on prey proximity model of Grey Wolf Optimizer to obtain least cost tournament schedule. We upgrade the position updating step of GWO by using probabilistic methods and hybridize it with SA to solve TTP and avoid getting stuck in local minima. Our proposed hybrid algorithm converges to an optimum solution for TTP. We calculate the overall cost of TTP and compare the performance of our alorithm with other metaheuristic algorithms like MBBO/ESA, BBO/SA, ACO and PSO.
基于灰狼优化器的旅行竞赛问题的改进启发式方法
本文提出了一种改进的启发式灰狼优化算法和模拟退火算法来求解旅行比赛问题的最优解。在本文中,我们研究了http的镜像版本。我们使用一种快速的建设性启发式算法来生成调度。在此基础上,结合灰狼优化器的猎物接近模型,提出了一种改进的启发式模拟退火方法,以获得成本最小的比赛计划。我们利用概率方法改进了GWO的位置更新步骤,并将其与SA混合求解TTP,避免陷入局部极小值。我们提出的混合算法收敛于TTP的最优解。我们计算了TTP的总成本,并将我们的算法与其他元启发式算法(如MBBO/ESA、BBO/SA、ACO和PSO)的性能进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信