Resource-constrained project scheduling problem with uncertain durations and renewable resources

Resource-constrained project scheduling problem is to make a schedule for minimization of the makespan subject to precedence and resource constraints. In this paper, we consider an uncertain resource-constrained project scheduling problem (URCPSP) in which the activity durations, with no historical...

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Bibliographic Details
Published in:International journal of machine learning and cybernetics Vol. 7; no. 4; pp. 613 - 621
Main Authors: Ma, Weimin, Che, Yangyang, Huang, Hu, Ke, Hua
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2016
Springer Nature B.V
Subjects:
Artificial Intelligence
Complex Systems
Computational Intelligence
Constraints
Control
Engineering
Expected values
Genetic algorithms
Mechatronics
Optimization
Original Article
Pattern Recognition
Project management
Random variables
Renewable resources
Resource scheduling
Robotics
Schedules
Scheduling
Systems Biology
United States > US
Resource-constrained project scheduling
Uncertain duration
Renewable resource
Genetic algorithm
Uncertainty theory
ISSN:1868-8071, 1868-808X
Online Access:Get full text
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Summary:Resource-constrained project scheduling problem is to make a schedule for minimization of the makespan subject to precedence and resource constraints. In this paper, we consider an uncertain resource-constrained project scheduling problem (URCPSP) in which the activity durations, with no historical data generally, are estimated by experts. In order to deal with these estimations, an uncertainty-theory-based project scheduling model is proposed. Furthermore, a genetic algorithm integrating a 99-method based uncertain simulation is designed to search the quasi-optimal schedule. Numerical examples are also provided to illustrate the effectiveness of the model and the algorithm.
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ISSN:1868-8071
1868-808X
DOI:10.1007/s13042-015-0444-4