Parallel-batch scheduling with rejection: Structural properties and approximation algorithms
•Parallel-batch scheduling with dynamic job arrivals and rejection.•Important structural properties are developed and skillfully applied.•A (3−1/b)-approximation algorithm with a complexity of O(nlogn).•An efficient PTAS with a complexity of O(nlogn+Cn). In this paper, we consider a parallel-batch m...
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Published in | European journal of operational research Vol. 310; no. 3; pp. 1017 - 1032 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
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01.11.2023
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Abstract | •Parallel-batch scheduling with dynamic job arrivals and rejection.•Important structural properties are developed and skillfully applied.•A (3−1/b)-approximation algorithm with a complexity of O(nlogn).•An efficient PTAS with a complexity of O(nlogn+Cn).
In this paper, we consider a parallel-batch machine scheduling (PBMS) model that unifies several existing scheduling models in the extant literature. In our scheduling model, a given set of jobs with different release dates are scheduled onto a machine that can process multiple jobs simultaneously in a batch. However, the number of jobs in a batch is limited. Each job can be rejected subject to a job-dependent penalty cost, but the total penalty cost of the jobs rejected is required to be no greater than a given bound. The objective is to minimize the weighted sum of the makespan of accepted jobs and the total rejection penalty of rejected jobs. We provide some important structural properties and develop fast approximation algorithms. We also present an efficient polynomial time approximation scheme (EPTAS) with near-linear-time complexity. Our results significantly improve both the time complexities and performance bounds of several existing algorithms and approximation schemes. |
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AbstractList | •Parallel-batch scheduling with dynamic job arrivals and rejection.•Important structural properties are developed and skillfully applied.•A (3−1/b)-approximation algorithm with a complexity of O(nlogn).•An efficient PTAS with a complexity of O(nlogn+Cn).
In this paper, we consider a parallel-batch machine scheduling (PBMS) model that unifies several existing scheduling models in the extant literature. In our scheduling model, a given set of jobs with different release dates are scheduled onto a machine that can process multiple jobs simultaneously in a batch. However, the number of jobs in a batch is limited. Each job can be rejected subject to a job-dependent penalty cost, but the total penalty cost of the jobs rejected is required to be no greater than a given bound. The objective is to minimize the weighted sum of the makespan of accepted jobs and the total rejection penalty of rejected jobs. We provide some important structural properties and develop fast approximation algorithms. We also present an efficient polynomial time approximation scheme (EPTAS) with near-linear-time complexity. Our results significantly improve both the time complexities and performance bounds of several existing algorithms and approximation schemes. |
Author | Lu, Lingfa Zhong, Xueling Ou, Jinwen |
Author_xml | – sequence: 1 givenname: Jinwen orcidid: 0000-0002-7419-3808 surname: Ou fullname: Ou, Jinwen email: toujinwen@jnu.edu.cn organization: School of Management, Jinan University, Guangzhou 510632, PR China – sequence: 2 givenname: Lingfa orcidid: 0000-0002-2561-5613 surname: Lu fullname: Lu, Lingfa email: lulingfa@zzu.edu.cn organization: School of Mathematics and Statistics, Zhengzhou University, Zhengzhou, Henan 450001, PR China – sequence: 3 givenname: Xueling orcidid: 0000-0002-5702-5837 surname: Zhong fullname: Zhong, Xueling email: tzhongxl@gduf.edu.cn organization: School of Internet Finance and Information Engineering, Guangdong University of Finance, Guangzhou 510521, PR China |
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Keywords | Rejection Worst-case analysis Scheduling Parallel-batch Approximation algorithm |
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SubjectTerms | Approximation algorithm Parallel-batch Rejection Scheduling Worst-case analysis |
Title | Parallel-batch scheduling with rejection: Structural properties and approximation algorithms |
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