{"title":"多维多容器包装的一种高效元启发式算法","authors":"G. Perboli, T. Crainic, R. Tadei","doi":"10.1109/CASE.2011.6042476","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce GASP - Greedy Adaptive Search Procedure, a metaheuristic able to efficiently address two and three-dimensional multiple container packing problems. GASP combines the simplicity of greedy algorithms with learning mechanisms aimed to guide the overall method towards good solutions. Extensive experiments indicate that GASP attains near-optimal solutions in very short computational times, and improves state-of-the-art results in comparable computational times.","PeriodicalId":236208,"journal":{"name":"2011 IEEE International Conference on Automation Science and Engineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":"{\"title\":\"An efficient metaheuristic for multi-dimensional multi-container packing\",\"authors\":\"G. Perboli, T. Crainic, R. Tadei\",\"doi\":\"10.1109/CASE.2011.6042476\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we introduce GASP - Greedy Adaptive Search Procedure, a metaheuristic able to efficiently address two and three-dimensional multiple container packing problems. GASP combines the simplicity of greedy algorithms with learning mechanisms aimed to guide the overall method towards good solutions. Extensive experiments indicate that GASP attains near-optimal solutions in very short computational times, and improves state-of-the-art results in comparable computational times.\",\"PeriodicalId\":236208,\"journal\":{\"name\":\"2011 IEEE International Conference on Automation Science and Engineering\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"29\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE International Conference on Automation Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CASE.2011.6042476\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Conference on Automation Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CASE.2011.6042476","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An efficient metaheuristic for multi-dimensional multi-container packing
In this paper, we introduce GASP - Greedy Adaptive Search Procedure, a metaheuristic able to efficiently address two and three-dimensional multiple container packing problems. GASP combines the simplicity of greedy algorithms with learning mechanisms aimed to guide the overall method towards good solutions. Extensive experiments indicate that GASP attains near-optimal solutions in very short computational times, and improves state-of-the-art results in comparable computational times.