Details
| Original language | English |
|---|---|
| Pages (from-to) | 379-391 |
| Number of pages | 13 |
| Journal | European Journal of Operational Research |
| Volume | 246 |
| Issue number | 2 |
| Publication status | Published - 16 Oct 2015 |
Abstract
In projects with a flexible project structure, the activities that must be scheduled are not completely known in advance. Scheduling such projects includes deciding whether to perform particular activities. This decision also affects precedence constraints among the implemented activities. However, established model formulations and solution approaches for the resource-constrained project scheduling problem (RCPSP) assume that the project structure is provided in advance. In this paper, the traditional RCPSP is extended using a highly general model-endogenous decision on this flexible project structure. This extension is illustrated using the example of the aircraft turnaround process at airports. We present a genetic algorithm to solve this type of scheduling problem and evaluate it in an extensive numerical study.
Keywords
- Flexible projects, Genetic algorithms, Project scheduling, RCPSP
ASJC Scopus subject areas
- Computer Science(all)
- General Computer Science
- Mathematics(all)
- Modelling and Simulation
- Decision Sciences(all)
- Management Science and Operations Research
- Decision Sciences(all)
- Information Systems and Management
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
In: European Journal of Operational Research, Vol. 246, No. 2, 16.10.2015, p. 379-391.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Scheduling resource-constrained projects with a flexible project structure
AU - Kellenbrink, Carolin
AU - Helber, Stefan
N1 - Publisher Copyright: © 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) with in the International Federation of Operational Research Societies (IFORS). All rights reserved. Copyright: Copyright 2015 Elsevier B.V., All rights reserved.
PY - 2015/10/16
Y1 - 2015/10/16
N2 - In projects with a flexible project structure, the activities that must be scheduled are not completely known in advance. Scheduling such projects includes deciding whether to perform particular activities. This decision also affects precedence constraints among the implemented activities. However, established model formulations and solution approaches for the resource-constrained project scheduling problem (RCPSP) assume that the project structure is provided in advance. In this paper, the traditional RCPSP is extended using a highly general model-endogenous decision on this flexible project structure. This extension is illustrated using the example of the aircraft turnaround process at airports. We present a genetic algorithm to solve this type of scheduling problem and evaluate it in an extensive numerical study.
AB - In projects with a flexible project structure, the activities that must be scheduled are not completely known in advance. Scheduling such projects includes deciding whether to perform particular activities. This decision also affects precedence constraints among the implemented activities. However, established model formulations and solution approaches for the resource-constrained project scheduling problem (RCPSP) assume that the project structure is provided in advance. In this paper, the traditional RCPSP is extended using a highly general model-endogenous decision on this flexible project structure. This extension is illustrated using the example of the aircraft turnaround process at airports. We present a genetic algorithm to solve this type of scheduling problem and evaluate it in an extensive numerical study.
KW - Flexible projects
KW - Genetic algorithms
KW - Project scheduling
KW - RCPSP
UR - http://www.scopus.com/inward/record.url?scp=84930872212&partnerID=8YFLogxK
U2 - 10.1016/j.ejor.2015.05.003
DO - 10.1016/j.ejor.2015.05.003
M3 - Article
VL - 246
SP - 379
EP - 391
JO - European Journal of Operational Research
JF - European Journal of Operational Research
SN - 0377-2217
IS - 2
ER -