{"title":"Economic Production with Poisson Demand, Lost Sales, a Constant Setup Time, and Fixed‐rate Discrete Replenishment","authors":"Thomas Schmitt, Bruce Faaland","doi":"10.1111/poms.14072","DOIUrl":null,"url":null,"abstract":"Abstract We address a production/inventory problem for a single product and machine where demand is Poisson distributed, and the times for unit production and setup are constant. Demand not in stock is lost. We derive a solution for a produce‐up‐to policy that minimizes average cost per‐unit‐time, including costs of setup, inventory carrying, and lost sales. The machine is stopped periodically, possibly rendered idle, set up for a fixed period, and then restarted. The average cost function, which we derive explicitly, is quasi‐convex separately in the produce‐up‐to level Q, the low‐level R that prompts a setup, and jointly in R equals Q. We start by finding the minimizing value of Q where R equals 0, and then extend the search over larger R values. The discrete search may end with R less than Q, or on the matrix diagonal where R equals Q, depending on the problem parameters. Idle time disappears in the cycle when R equals Q, and the two parameter system folds into one. This hybrid policy is novel in make‐to‐stock problems with a setup time. The number of arithmetic operations to calculate costs in the (Q,R) matrix depends on a vector search over Q. The computation of the algorithm is bounded by a quadratic function of the minimizing value of Q. The storage requirements and number of cells visited are proportional to it. This article is protected by copyright. All rights reserved","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":"8 1","pages":"0"},"PeriodicalIF":4.8000,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Production and Operations Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/poms.14072","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract We address a production/inventory problem for a single product and machine where demand is Poisson distributed, and the times for unit production and setup are constant. Demand not in stock is lost. We derive a solution for a produce‐up‐to policy that minimizes average cost per‐unit‐time, including costs of setup, inventory carrying, and lost sales. The machine is stopped periodically, possibly rendered idle, set up for a fixed period, and then restarted. The average cost function, which we derive explicitly, is quasi‐convex separately in the produce‐up‐to level Q, the low‐level R that prompts a setup, and jointly in R equals Q. We start by finding the minimizing value of Q where R equals 0, and then extend the search over larger R values. The discrete search may end with R less than Q, or on the matrix diagonal where R equals Q, depending on the problem parameters. Idle time disappears in the cycle when R equals Q, and the two parameter system folds into one. This hybrid policy is novel in make‐to‐stock problems with a setup time. The number of arithmetic operations to calculate costs in the (Q,R) matrix depends on a vector search over Q. The computation of the algorithm is bounded by a quadratic function of the minimizing value of Q. The storage requirements and number of cells visited are proportional to it. This article is protected by copyright. All rights reserved
期刊介绍:
The mission of Production and Operations Management is to serve as the flagship research journal in operations management in manufacturing and services. The journal publishes scientific research into the problems, interest, and concerns of managers who manage product and process design, operations, and supply chains. It covers all topics in product and process design, operations, and supply chain management and welcomes papers using any research paradigm.