{"title":"实践摘要：通用电气公司优化风力涡轮机塔架采购和物流业务","authors":"Srinivas Bollapragada","doi":"10.1287/inte.2022.0058","DOIUrl":null,"url":null,"abstract":"General Electric’s Renewable Energy business used to manually make annual sourcing and logistics plans to procure wind turbine towers from suppliers across the world and deliver them to customer sites. This process was time-consuming, cumbersome, suboptimal, and increased the cost of fulfilling customer demands. We developed an algorithm and a software tool to generate near-optimal towers’ sourcing and logistics plans, which minimized the total direct material and logistics costs incurred.","PeriodicalId":510763,"journal":{"name":"INFORMS Journal on Applied Analytics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Practice Summary: General Electric Company Optimizes Wind Turbine Towers Sourcing and Logistics Operations\",\"authors\":\"Srinivas Bollapragada\",\"doi\":\"10.1287/inte.2022.0058\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"General Electric’s Renewable Energy business used to manually make annual sourcing and logistics plans to procure wind turbine towers from suppliers across the world and deliver them to customer sites. This process was time-consuming, cumbersome, suboptimal, and increased the cost of fulfilling customer demands. We developed an algorithm and a software tool to generate near-optimal towers’ sourcing and logistics plans, which minimized the total direct material and logistics costs incurred.\",\"PeriodicalId\":510763,\"journal\":{\"name\":\"INFORMS Journal on Applied Analytics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"INFORMS Journal on Applied Analytics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1287/inte.2022.0058\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"INFORMS Journal on Applied Analytics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1287/inte.2022.0058","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Practice Summary: General Electric Company Optimizes Wind Turbine Towers Sourcing and Logistics Operations
General Electric’s Renewable Energy business used to manually make annual sourcing and logistics plans to procure wind turbine towers from suppliers across the world and deliver them to customer sites. This process was time-consuming, cumbersome, suboptimal, and increased the cost of fulfilling customer demands. We developed an algorithm and a software tool to generate near-optimal towers’ sourcing and logistics plans, which minimized the total direct material and logistics costs incurred.
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