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Resource leveling with subcontracting: algorithms and complexity.

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Title: Resource leveling with subcontracting: algorithms and complexity.
Authors: Hall, Nicholas G.1 (AUTHOR) hall.33@osu.edu, Posner, Marc E.2 (AUTHOR)
Source: Journal of Scheduling. Feb2026, Vol. 29 Issue 1, p39-50. 12p.
Subjects: Subcontracting, Algorithms, Scheduling, Computational complexity, Project management, Resource allocation
Abstract: A central problem in project management is the optimal use of limited resources. We consider the resource leveling problem, which minimizes the maximum resource load over the life of a project. This problem is motivated by the need to limit expensive resource acquisition. For several variants of this problem, we either provide an efficient optimal algorithm or show that the problem is intractable. We also consider a generalization of the resource leveling problem where work can be subcontracted. The subcontracting cost is defined either by task or by time of subcontracting. Our results show how the solvability of resource leveling problems depends on whether task times are unit or arbitrary, whether resource requirements are unit or binary, whether the project network is a chain, a tree, or an opposing forest, whether subcontracting costs for jobs are unit or binary, and whether the availability of subcontracting at a time period is constrained. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Scheduling is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Resource leveling with subcontracting: algorithms and complexity.
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  Data: <searchLink fieldCode="DE" term="%22Subcontracting%22">Subcontracting</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Scheduling%22">Scheduling</searchLink><br /><searchLink fieldCode="DE" term="%22Computational+complexity%22">Computational complexity</searchLink><br /><searchLink fieldCode="DE" term="%22Project+management%22">Project management</searchLink><br /><searchLink fieldCode="DE" term="%22Resource+allocation%22">Resource allocation</searchLink>
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  Data: A central problem in project management is the optimal use of limited resources. We consider the resource leveling problem, which minimizes the maximum resource load over the life of a project. This problem is motivated by the need to limit expensive resource acquisition. For several variants of this problem, we either provide an efficient optimal algorithm or show that the problem is intractable. We also consider a generalization of the resource leveling problem where work can be subcontracted. The subcontracting cost is defined either by task or by time of subcontracting. Our results show how the solvability of resource leveling problems depends on whether task times are unit or arbitrary, whether resource requirements are unit or binary, whether the project network is a chain, a tree, or an opposing forest, whether subcontracting costs for jobs are unit or binary, and whether the availability of subcontracting at a time period is constrained. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Scheduling is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s10951-025-00861-0
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        Text: English
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        StartPage: 39
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      – SubjectFull: Subcontracting
        Type: general
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Scheduling
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      – SubjectFull: Computational complexity
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      – SubjectFull: Project management
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      – SubjectFull: Resource allocation
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              Text: Feb2026
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