{"title":"Scheduling method of maintenance support resource with task timing constraint","authors":"Chongchong Guan, Hui Lu","doi":"10.1109/SSCI44817.2019.9003132","DOIUrl":null,"url":null,"abstract":"Maintenance support resource scheduling (MSRS) problem has attracted increasing attention in modern battle. It aims to allocate resources from multi-supply points to multi-tasks with the shortest time. However, there exists various constraints which are difficult to satisfy at the same time, such as limited resource reserves, different resource requirements, complex route conditions and strict task timing. As a result, we first obtain the shortest routes and task sequence with route planning and topological sorting algorithms separately. Then, with these information, an integrated meta-heuristic algorithm (IMHA) is designed to solve all the constraints. Furthermore, two improved algorithms, CMHA and GMHA are generated with classical and greedy scheduling strategies respectively. Experiment results show the feasibility of IMHA in solving the MSRS problem with timing constraint. Besides, compared with the IMHA, the GMHA and CMHA can generate scheduling schemes with lower cost and time in the whole 24 instances. In addition, as the increase of proportion of timing tasks, the advantages of GMHA in cost and time are more evident.","PeriodicalId":6729,"journal":{"name":"2019 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"154 1","pages":"2698-2705"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Symposium Series on Computational Intelligence (SSCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSCI44817.2019.9003132","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Maintenance support resource scheduling (MSRS) problem has attracted increasing attention in modern battle. It aims to allocate resources from multi-supply points to multi-tasks with the shortest time. However, there exists various constraints which are difficult to satisfy at the same time, such as limited resource reserves, different resource requirements, complex route conditions and strict task timing. As a result, we first obtain the shortest routes and task sequence with route planning and topological sorting algorithms separately. Then, with these information, an integrated meta-heuristic algorithm (IMHA) is designed to solve all the constraints. Furthermore, two improved algorithms, CMHA and GMHA are generated with classical and greedy scheduling strategies respectively. Experiment results show the feasibility of IMHA in solving the MSRS problem with timing constraint. Besides, compared with the IMHA, the GMHA and CMHA can generate scheduling schemes with lower cost and time in the whole 24 instances. In addition, as the increase of proportion of timing tasks, the advantages of GMHA in cost and time are more evident.