运筹与管理2018，Vol.27Issue(1)：53-58,6.DOI:10.12005/orms.2018.0009
带学习效应和资源依赖的单机排序模型
Single Machine Scheduling Problems with Learning Effect and Resource-dependence
摘要
Abstract
In industrial manufactures,the time spent on the same task will be reduced as the skill level of the staff increases.At the same time,the manager will consider allocating a certain amount of additional resources to shorten the job processing time.In this paper,we consider single machine scheduling problems in which the actual processing time of a job is of learning effect and of resource-dependence based on the above case.In the problem,it is assumed that the actual processing time of a job is an exponential function of the total normal processing time of jobs already processed before it.At the same time,the actual processing time of a job linear decreases and the total resource consumption costs linear increases as the resource distributed to the job increases.For such a scheduling problem,we introduce five objective functions:the sum of makespan and total resource consumption costs;the sum of the total completion time and total resource consumption costs;the sum of the total weighted completion time and total resource consumption costs;the sum of the total earliness、tardi-ness、common due date and total resource consumption costs and the sum of the total earliness、tardiness、slack due date and total resource consumption costs.For the scheduling problems corresponding to the first three func-tions,we present polynomial time solvable algorithms respectively.We give time solvable algorithms for the scheduling problems corresponding to the last two functions respectively by using assignment problem.关键词
单机排序/学习效应/资源依赖/指派问题Key words
single machine scheduling problem/learning effect/resource-dependent/assignment problem分类
数理科学引用本文复制引用
余英,程明宝..带学习效应和资源依赖的单机排序模型[J].运筹与管理,2018,27(1):53-58,6.基金项目
贵州省科技厅与凯里学院2014年度省校合作协议项目:基于共同交货期的提前延误排序问题(黔科合LH字[2014]7232) （黔科合LH字[2014]7232）
贵州凯里学院院级科研课题重点课题:考虑资源有限性的资源配置与调度优化研究(Z1602) （Z1602）
国家自然科学基金项目:考虑患者意愿的关键医疗资源配置与调度优化研究(71571050) （71571050）
本论文得到国家留学基金的资助 （）
