运筹与管理 ›› 2020, Vol. 29 ›› Issue (1): 223-239.DOI: 10.12005/orms.2020.0027

• 综述 • 上一篇    

并行分批排序综述

井彩霞1, 吴瑞强2, 贾兆红3   

  1. 1. 天津工业大学 经济与管理学院,天津 300387;
    2. 天津曙光存储科技有限公司 存储产品研发部,天津 300384;
    3. 安徽大学 计算机科学与技术学院,安徽 合肥 230601
  • 收稿日期:2018-09-21 出版日期:2020-01-25
  • 作者简介:井彩霞(1980-), 女, 河北承德人, 副教授, 博士, 主要研究方向为排序与调度优化;吴瑞强(1980-), 男, 河北承德人, 硕士, 主要从事软件的研发及应用;贾兆红(1976-), 女, 安徽巢湖人, 教授, 博士, 主要研究方向为计算智能和多目标优化。
  • 基金资助:
    天津市高等学校创新团队培养计划(TD13-5038);国家自然科学基金(71971002);教育部青年基金资助项目(15YJC630041);安徽省自然科学基金资助项目(1608085MG154)

A Review of Parallel Batch Scheduling

JING Cai-xia1, WU Rui-qiang2, JIA Zhao-hong3   

  1. 1. School of Economics and Management, Tiangong University, Tianjin 300387, China;
    2. Research and Development Center, Tianjin Dawning Storage Technology Limited Company, Tianjin 300384, China;
    3. School of Computer Science and Technology, Anhui University, Hefei 230601, China
  • Received:2018-09-21 Online:2020-01-25

摘要: 并行分批排序起源于半导体芯片制造过程。在并行分批排序中,工件可成批加工,批加工机器最多可同时加工B个工件,批的加工时间为批中所有工件的最大工时。首先根据传统的机器环境和目标函数对并行分批排序已有成果进行分类介绍,主要为单机和平行机的机器环境,以及极小化最大完工时间、极小化总完工时间、极小化最大延迟、极小化误工工件数、极小化总延误和极小化最大延误的目标函数;然后梳理了由基本问题所衍生出来的具有新特点的16类新型并行分批排序,包括差异尺寸工件、多目标、工件加工时间或顺序存在限制、考虑费用和具有特殊机制等情况;最后展望未来的研究方向。

关键词: 并行分批排序, 时间复杂性, 启发式算法, 智能算法, 近似算法, 综述

Abstract: Parallel batch scheduling arises from semiconductor manufacturing. In this type of scheduling, jobs are processed in batch and the batch processing machine is capable of processing up to B jobs simultaneously as a batch. The processing time of a batch is equal to the longest processing time of the jobs in the batch. Firstly, achievements of parallel batch scheduling with different traditional machine environments and objective functions are introduced, where machine environments mainly refer to single machine and parallel machines, and objective functions are makespan, total completion time, maximum lateness, number of tardy jobs, total tardiness and maximum tardiness; then 16 new problems derived from general problems by combining with new characteristics are classified, and they are parallel batch scheduling problems with non-identical job sizes, problems with multi-objectives or new objectives, problems subject to precedence constraints, problems with transportation time, discretely controllable processing time, deteriorating jobs, learning effect, forbidden intervals, due windows, energy consumption consideration, rejection, bathing cost, job processing time compatibilities, two-agent, rescheduling and semi-continuous respectively; and research directions of parallel batch scheduling in the future are looked forward to at last.

Key words: parallel batch scheduling, time complexity, heuristic, intelligent algorithm, approximation algorithm, review

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