{"title":"Hybridized Ant Colony System for Tasks to Workstations Assignment","authors":"A. Serbencu, V. Mînzu","doi":"10.1109/SSCI.2016.7850060","DOIUrl":null,"url":null,"abstract":"Ant Colony System is a well-known metaheuristic used to solve combinatorial optimization problems that is not intrinsically prepared to deal with precedence constraints. The work reported here is the continuation of the results presented in a previous paper that proposed an Ant System algorithm devoted to Tasks to Workstations Assignment problem. A special technique was developed in order to increase the effectiveness of precedence constraints treatment. On the one hand the contribution of this paper consists in the amelioration of this technique. On the other hand, the Ant System algorithm is hybridized with a local descent deterministic algorithm that contributes greatly to the avoiding of solutions bias. The results of the hybridized Ant System algorithm have proved the effectiveness of the proposed way to treat the precedence constraints","PeriodicalId":120288,"journal":{"name":"2016 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Symposium Series on Computational Intelligence (SSCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSCI.2016.7850060","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Ant Colony System is a well-known metaheuristic used to solve combinatorial optimization problems that is not intrinsically prepared to deal with precedence constraints. The work reported here is the continuation of the results presented in a previous paper that proposed an Ant System algorithm devoted to Tasks to Workstations Assignment problem. A special technique was developed in order to increase the effectiveness of precedence constraints treatment. On the one hand the contribution of this paper consists in the amelioration of this technique. On the other hand, the Ant System algorithm is hybridized with a local descent deterministic algorithm that contributes greatly to the avoiding of solutions bias. The results of the hybridized Ant System algorithm have proved the effectiveness of the proposed way to treat the precedence constraints