An efficient polynomial-time approximation scheme for parallel multi-stage open shops

[2205.14407] An efficient polynomial-time approximation scheme for parallel multi-stage open shops Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Data Structures and Algorithms arXiv:2205.14407 (cs) [Submitted on 28 May 2022] Title: An efficient polynomial-time approximation scheme for parallel multi-stage open shops Authors: Jianming Dong , Ruyan Jin , Guohui Lin , Bing Su , Weitian Tong , Yao Xu View a PDF of the paper titled An efficient polynomial-time approximation scheme for parallel multi-stage open shops, by Jianming Dong and 5 other authors View PDF HTML (experimental) Abstract: Various new scheduling problems have been arising from practical production processes and spawning new research areas in the scheduling field. We study the parallel multi-stage open shops problem, which generalizes the classic open shop scheduling and parallel machine scheduling problems. Given m identical k-stage open shops and a set of n jobs, we aim to process all jobs on these open shops with the minimum makespan, i.e., the completion time of the last job, under the constraint that job preemption is not allowed. We present an efficient polynomial-time approximation scheme (EPTAS) for the case when both m and k are constant. The main idea for our EPTAS is the combination of several categorization, scaling, and linear programming rounding techniques. Jobs and/or operations are first scaled and then categorized carefully into multiple types so that different types of jobs and/or operations are scheduled appropriately without increasing the makespan too much. Subjects: Data Structures and Algorithms (cs.DS) Cite as: arXiv:2205.14407 [cs.DS] (or arXiv:2205.14407v1 [cs.DS] for this version) https://doi.org/10.48550/arXiv.2205.14407 Focus to learn more arXiv-issued DOI via DataCite Related DOI : https://doi.org/10.1016/j.dam.2025.08.004 Focus to learn more DOI(s) linking to related resources Submission history From: Weitian Tong [ view email ] [v1] Sat, 28 May 2022 11:46:37 UTC (22 KB) Full-text links: Access Paper: View a PDF of the paper titled An efficient polynomial-time approximation scheme for parallel multi-stage open shops, by Jianming Dong and 5 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.DS < prev | next > new | recent | 2022-05 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

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