{"title":"为按顺序购买的异质客户定价的异质产品","authors":"Refael Hassin, Justo Puerto","doi":"10.1007/s10479-024-06133-y","DOIUrl":null,"url":null,"abstract":"<div><p>This paper considers optimal pricing in a system with limited substitutable resources, such as certain goods or services. Prices for the different resources have to be set and then customers with heterogeneous preferences show up sequentially. Customers, of <i>n</i> types, select an item from the <i>m</i> available resources, depending on their valuations of the resources and the prices. The goal is to analyze this optimization problem, characterize a set of candidates to optimal solutions and provide methods for solving it. We prove that this problem is NP-hard to approximate within a factor <span>\\(O(n^{1-\\varepsilon })\\)</span> for any fixed <span>\\(\\varepsilon >0\\)</span>. Another important contribution is to prove that, the space of prices (which in principle is a continuous domain in <span>\\({\\mathbb {R}}^m\\)</span>), can be reduced to a finite set of vectors of cardinality <span>\\(m^{m-2}n^m2^m\\)</span>. For a deterministic version of the problem, where the customer types are known to the firm, we provide a mathematical program that chooses the best set of prices. We report extensive computational results showing the usefulness of our exact approach to solve medium size problems with up to 200 customers and different assortments of products and customer types. We then show how to approximate the stochastic model by a small number of solutions of deterministic scenarios solved using a mixed-integer linear program.</p></div>","PeriodicalId":8215,"journal":{"name":"Annals of Operations Research","volume":"340 2-3","pages":"863 - 890"},"PeriodicalIF":4.4000,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10479-024-06133-y.pdf","citationCount":"0","resultStr":"{\"title\":\"Pricing heterogeneous products to heterogeneous customers who buy sequentially\",\"authors\":\"Refael Hassin, Justo Puerto\",\"doi\":\"10.1007/s10479-024-06133-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This paper considers optimal pricing in a system with limited substitutable resources, such as certain goods or services. Prices for the different resources have to be set and then customers with heterogeneous preferences show up sequentially. Customers, of <i>n</i> types, select an item from the <i>m</i> available resources, depending on their valuations of the resources and the prices. The goal is to analyze this optimization problem, characterize a set of candidates to optimal solutions and provide methods for solving it. We prove that this problem is NP-hard to approximate within a factor <span>\\\\(O(n^{1-\\\\varepsilon })\\\\)</span> for any fixed <span>\\\\(\\\\varepsilon >0\\\\)</span>. Another important contribution is to prove that, the space of prices (which in principle is a continuous domain in <span>\\\\({\\\\mathbb {R}}^m\\\\)</span>), can be reduced to a finite set of vectors of cardinality <span>\\\\(m^{m-2}n^m2^m\\\\)</span>. For a deterministic version of the problem, where the customer types are known to the firm, we provide a mathematical program that chooses the best set of prices. We report extensive computational results showing the usefulness of our exact approach to solve medium size problems with up to 200 customers and different assortments of products and customer types. We then show how to approximate the stochastic model by a small number of solutions of deterministic scenarios solved using a mixed-integer linear program.</p></div>\",\"PeriodicalId\":8215,\"journal\":{\"name\":\"Annals of Operations Research\",\"volume\":\"340 2-3\",\"pages\":\"863 - 890\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2024-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s10479-024-06133-y.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annals of Operations Research\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s10479-024-06133-y\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"OPERATIONS RESEARCH & MANAGEMENT SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Operations Research","FirstCategoryId":"91","ListUrlMain":"https://link.springer.com/article/10.1007/s10479-024-06133-y","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
Pricing heterogeneous products to heterogeneous customers who buy sequentially
This paper considers optimal pricing in a system with limited substitutable resources, such as certain goods or services. Prices for the different resources have to be set and then customers with heterogeneous preferences show up sequentially. Customers, of n types, select an item from the m available resources, depending on their valuations of the resources and the prices. The goal is to analyze this optimization problem, characterize a set of candidates to optimal solutions and provide methods for solving it. We prove that this problem is NP-hard to approximate within a factor \(O(n^{1-\varepsilon })\) for any fixed \(\varepsilon >0\). Another important contribution is to prove that, the space of prices (which in principle is a continuous domain in \({\mathbb {R}}^m\)), can be reduced to a finite set of vectors of cardinality \(m^{m-2}n^m2^m\). For a deterministic version of the problem, where the customer types are known to the firm, we provide a mathematical program that chooses the best set of prices. We report extensive computational results showing the usefulness of our exact approach to solve medium size problems with up to 200 customers and different assortments of products and customer types. We then show how to approximate the stochastic model by a small number of solutions of deterministic scenarios solved using a mixed-integer linear program.
期刊介绍:
The Annals of Operations Research publishes peer-reviewed original articles dealing with key aspects of operations research, including theory, practice, and computation. The journal publishes full-length research articles, short notes, expositions and surveys, reports on computational studies, and case studies that present new and innovative practical applications.
In addition to regular issues, the journal publishes periodic special volumes that focus on defined fields of operations research, ranging from the highly theoretical to the algorithmic and the applied. These volumes have one or more Guest Editors who are responsible for collecting the papers and overseeing the refereeing process.