research-article

New complexity and approximability results for minimizing the total weighted completion time on a single machine subject to non-renewable resource constraints

Authors:

Péter Györgyi,

Tamás KisAuthors Info & Claims

Volume 311, Issue C

Pages 97 - 109

https://doi.org/10.1016/j.dam.2022.01.009

Published: 15 April 2022 Publication History

Abstract

We consider single machine scheduling problems with additional non-renewable resource constraints. Examples for non-renewable resources include raw materials, energy, or money. Usually they have an initial stock and replenishments arrive over time at a-priori known time points and quantities. The jobs have some requirements from the resources and a job can only be started if the available quantity from each of the required resources exceeds the requirements of the job. Upon starting a job, it consumes its requirements which decreases the available quantities of the respective non-renewable resources. There is a broad background for this class of problems. Most of the literature concentrate on the makespan, and the maximum lateness objectives. This paper focuses on the total weighted completion time objective for which the list of the approximation algorithms is very short. We extend that list by considering new special cases and obtain new complexity results and approximation algorithms.

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Cited By

Bentert MBredereck RGyörgyi PKaczmarczyk ANiedermeier R(2023)A multivariate complexity analysis of the material consumption scheduling problemJournal of Scheduling10.1007/s10951-022-00771-526:4(369-382)Online publication date: 1-Aug-2023
https://dl.acm.org/doi/10.1007/s10951-022-00771-5

Index Terms

New complexity and approximability results for minimizing the total weighted completion time on a single machine subject to non-renewable resource constraints
1. Mathematics of computing
  1. Mathematical analysis
2. Theory of computation
  1. Design and analysis of algorithms
    1. Approximation algorithms analysis
      1. Scheduling algorithms
    2. Online algorithms
      1. Online learning algorithms
        Scheduling algorithms
  2. Theory and algorithms for application domains
    1. Machine learning theory
      1. Reinforcement learning
        Sequential decision making

Index terms have been assigned to the content through auto-classification.

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Published In

cover image Discrete Applied Mathematics

Discrete Applied Mathematics Volume 311, Issue C

Apr 2022

154 pages

ISSN:0166-218X

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 15 April 2022

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Cited By

Bentert MBredereck RGyörgyi PKaczmarczyk ANiedermeier R(2023)A multivariate complexity analysis of the material consumption scheduling problemJournal of Scheduling10.1007/s10951-022-00771-526:4(369-382)Online publication date: 1-Aug-2023
https://dl.acm.org/doi/10.1007/s10951-022-00771-5

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