{"title":"Adaptive Genetic Hybrids for Order Review and Release into Production","authors":"A. Orsoni","doi":"10.1109/IS.2006.348521","DOIUrl":null,"url":null,"abstract":"Over recent years order review and release (ORR) has attracted increasing attention in manufacturing research due to its important impact on production performance. By means of effectively controlling the rate of input of jobs into the production system, in fact, the sustainability of feasible and economical production levels can be significantly enhanced. In this context of research the paper proposes a hybrid decision support system (DSS) to address the simultaneous review of multiple incoming orders and, thereby, support better informed acceptance and rejection decisions. The DSS, as developed for this research, relies on the interactive use of simulation and adaptive genetic hybrids, integrating local and global search techniques, to identify the combination of accepted orders that maximizes production performance while reducing the risk of accepting sub-optimal combinations","PeriodicalId":116809,"journal":{"name":"2006 3rd International IEEE Conference Intelligent Systems","volume":"100 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 3rd International IEEE Conference Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IS.2006.348521","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Over recent years order review and release (ORR) has attracted increasing attention in manufacturing research due to its important impact on production performance. By means of effectively controlling the rate of input of jobs into the production system, in fact, the sustainability of feasible and economical production levels can be significantly enhanced. In this context of research the paper proposes a hybrid decision support system (DSS) to address the simultaneous review of multiple incoming orders and, thereby, support better informed acceptance and rejection decisions. The DSS, as developed for this research, relies on the interactive use of simulation and adaptive genetic hybrids, integrating local and global search techniques, to identify the combination of accepted orders that maximizes production performance while reducing the risk of accepting sub-optimal combinations
订单审核与放行(order review and release, ORR)由于其对生产绩效的重要影响,近年来越来越受到制造业研究的关注。事实上,通过有效控制工作投入生产系统的速度,可以显著提高可行和经济生产水平的可持续性。在此研究背景下,本文提出了一种混合决策支持系统(DSS)来解决同时审查多个传入订单的问题,从而支持更明智的接受和拒绝决策。为本研究开发的DSS依赖于模拟和自适应遗传杂交的交互式使用,集成了局部和全局搜索技术,以确定可接受的订单组合,从而最大化生产性能,同时降低接受次优组合的风险