{"title":"Oz Scheduler: a workbench for scheduling problems","authors":"J. Würtz","doi":"10.1109/TAI.1996.560445","DOIUrl":null,"url":null,"abstract":"This paper describes the Oz Scheduler; a workbench for scheduling problems. Through a graphical interface, the user can freely combine the elements that define a scheduling strategy. Such elements include constraints with different propagation behavior or distribution and search strategies. Exploring the possible combinations can lead to better solutions. Recent and successful techniques for scheduling are incorporated. Resulting from the selections made, a constraint problem is generated dynamically. For this problem, the solution statistics and the search can be inspected by several graphical tools. The functionality can be extended by sending messages to the Scheduler. The functionality and the implementation of the Oz Scheduler are discussed. The overall performance of the Scheduler for standard benchmarks is comparable to state-of-the-art special-purpose systems for scheduling. The implementation is based on the concurrent constraint language Oz.","PeriodicalId":209171,"journal":{"name":"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAI.1996.560445","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 22
Abstract
This paper describes the Oz Scheduler; a workbench for scheduling problems. Through a graphical interface, the user can freely combine the elements that define a scheduling strategy. Such elements include constraints with different propagation behavior or distribution and search strategies. Exploring the possible combinations can lead to better solutions. Recent and successful techniques for scheduling are incorporated. Resulting from the selections made, a constraint problem is generated dynamically. For this problem, the solution statistics and the search can be inspected by several graphical tools. The functionality can be extended by sending messages to the Scheduler. The functionality and the implementation of the Oz Scheduler are discussed. The overall performance of the Scheduler for standard benchmarks is comparable to state-of-the-art special-purpose systems for scheduling. The implementation is based on the concurrent constraint language Oz.