{"title":"Inventory placement on a network","authors":"John R. Birge, Levi DeValve","doi":"10.1016/j.orl.2025.107240","DOIUrl":null,"url":null,"abstract":"<div><div>We consider the problem of placing inventory on a network in advance of uncertain demand, in order to minimize the sum of inventory placement costs and expected fulfillment and shortage costs. Complexity results (in terms of inapproximability lower bounds) are derived under different assumptions. Then we develop two approximation guarantees: one is asymptotically optimal as demand grows large, and the other provides a constant guarantee with metric fulfillment costs.</div></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":"60 ","pages":"Article 107240"},"PeriodicalIF":0.8000,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Operations Research Letters","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S016763772500001X","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
We consider the problem of placing inventory on a network in advance of uncertain demand, in order to minimize the sum of inventory placement costs and expected fulfillment and shortage costs. Complexity results (in terms of inapproximability lower bounds) are derived under different assumptions. Then we develop two approximation guarantees: one is asymptotically optimal as demand grows large, and the other provides a constant guarantee with metric fulfillment costs.
期刊介绍：
Operations Research Letters is committed to the rapid review and fast publication of short articles on all aspects of operations research and analytics. Apart from a limitation to eight journal pages, quality, originality, relevance and clarity are the only criteria for selecting the papers to be published. ORL covers the broad field of optimization, stochastic models and game theory. Specific areas of interest include networks, routing, location, queueing, scheduling, inventory, reliability, and financial engineering. We wish to explore interfaces with other fields such as life sciences and health care, artificial intelligence and machine learning, energy distribution, and computational social sciences and humanities. Our traditional strength is in methodology, including theory, modelling, algorithms and computational studies. We also welcome novel applications and concise literature reviews.
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