{"title":"Common due window assignment and single machine scheduling with delivery time, resource allocation, and job-dependent learning effect","authors":"Jin Qian, Zhiyuan Guo","doi":"10.1007/s12190-024-02090-8","DOIUrl":null,"url":null,"abstract":"<p>A single machine scheduling problem takes into account a common due window assignment, including delivery time, resource allocation and learning effect. The basic processing time, position and allotted resources are all linked to the actual processing time. We take into consideration three goal functions, which minimize the costs of earliness, tardiness, start time of window, window size, resource allocation and makespan. The aim is to find the optimal sequence and distribution of resources. Polynomial time algorithms are provided for each of the three issues. The algorithms have <span>\\(O(n^3)\\)</span> levels of complexity, where <i>n</i> is the number of jobs. Special cases with the same learning rates are also considered. Polynomial time algorithms are also provided for each of the special cases. The algorithms have <span>\\(O(n\\textrm{log}n)\\)</span> levels of complexity.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s12190-024-02090-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
A single machine scheduling problem takes into account a common due window assignment, including delivery time, resource allocation and learning effect. The basic processing time, position and allotted resources are all linked to the actual processing time. We take into consideration three goal functions, which minimize the costs of earliness, tardiness, start time of window, window size, resource allocation and makespan. The aim is to find the optimal sequence and distribution of resources. Polynomial time algorithms are provided for each of the three issues. The algorithms have \(O(n^3)\) levels of complexity, where n is the number of jobs. Special cases with the same learning rates are also considered. Polynomial time algorithms are also provided for each of the special cases. The algorithms have \(O(n\textrm{log}n)\) levels of complexity.