An event-based reactive scheduling approach for the Resource Constrained Project Scheduling Problem with unreliable resources
The Resource Constrained Project Scheduling Problem (RCPSP) is a combinatorial optimization problem which is non-deterministic polynomial-time (NP)-hard in nature. Due to the diversified applications of RCPSPs, they have been commonly used as scheduling procedures in real-world problems. Since, in p...
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| Vydáno v: | Computers & industrial engineering Ročník 151; s. 106981 |
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| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier Ltd
01.01.2021
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| Témata: | |
| ISSN: | 0360-8352, 1879-0550 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | The Resource Constrained Project Scheduling Problem (RCPSP) is a combinatorial optimization problem which is non-deterministic polynomial-time (NP)-hard in nature. Due to the diversified applications of RCPSPs, they have been commonly used as scheduling procedures in real-world problems. Since, in practice, project data are prone to changes or disruptions, this paper introduces a mathematical model for a reactive scheduling approach, called the Event Based Reactive Approach (EBRA). This proposed EBRA approach is employed to examine its recovery performance under both a single disruption and a series of independent resource disruptions. Several simulated disruption data are hypothesized to represent real-world disruption scenarios and, without loss of generality, the proposed reactive approach is proved to be efficient in reducing the number of variables and computational complexity and also to be resilient in realistic changes, such as duration inflation and dynamic resource usages. Along with employing an exact method by LINGO software, this paper also proposes an enhanced iterated greedy (EnIG) approach to meta-heuristically solve larger and computationally expensive benchmark instances taken from the Project Scheduling Library (PSPLIB).
•Formulated one event based reactive model to deal with disruption scenarios.•A solution approach is proposed to generate a revised schedule after disruptions.•Comparative evaluation of two different reactive strategies are carried out.•The model is capable of dealing with a single, as well as multiple disruptions. |
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| ISSN: | 0360-8352 1879-0550 |
| DOI: | 10.1016/j.cie.2020.106981 |