{"title":"On stockpile planning using a multi-objective genetic algorithm","authors":"R. Pall, E. Cheung","doi":"10.1109/CIMSA.2011.6059911","DOIUrl":null,"url":null,"abstract":"The North Atlantic Treaty Organization (NATO) Stockpile Planning Committee (SPC) periodically determines if NATO member nations have the necessary munitions for a full range of mission types, accomplished through the use of a model that minimizes the cost of the required stockpile. We were tasked to examine how the methodology of this model could be modified to allow individual nations to better determine their requirements for Precision-Guided Munitions (PGMs). The approach we undertook involves augmenting the methodology of the model with a multi-objective optimization approach using a genetic algorithm, in which the solution is optimized along two competing objectives: total cost (which is minimized), and the usage of PGMs (which is maximized). We recommended that the SPC consider including this change in all future versions of ACROSS.","PeriodicalId":422972,"journal":{"name":"2011 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA) Proceedings","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA) Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIMSA.2011.6059911","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
The North Atlantic Treaty Organization (NATO) Stockpile Planning Committee (SPC) periodically determines if NATO member nations have the necessary munitions for a full range of mission types, accomplished through the use of a model that minimizes the cost of the required stockpile. We were tasked to examine how the methodology of this model could be modified to allow individual nations to better determine their requirements for Precision-Guided Munitions (PGMs). The approach we undertook involves augmenting the methodology of the model with a multi-objective optimization approach using a genetic algorithm, in which the solution is optimized along two competing objectives: total cost (which is minimized), and the usage of PGMs (which is maximized). We recommended that the SPC consider including this change in all future versions of ACROSS.