A robust bi-objective model for concurrent planning of project scheduling and material procurement

•A bi-objective model for simultaneous project scheduling and material procurement.•Addressing both project schedule and total costs robustness.•Possibility to procure materials from varied suppliers with discount utilization.•Application of tuned meta-heuristics to solve the model of different size...

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Bibliographic Details
Published in:Computers & industrial engineering Vol. 98; pp. 11 - 29
Main Authors: Tabrizi, Babak H., Ghaderi, Seyed Farid
Format: Journal Article
Language:English
Published: New York Elsevier Ltd 01.08.2016
Pergamon Press Inc
Subjects:
Calibration
Corporate purchasing
Cost reduction
Costs
Genetic algorithms
Integer programming
Material procurement
Mathematical analysis
Mathematical models
Procurement
Programming
Project management
Project scheduling
Robust optimization
Robustness
Scheduling
Studies
Taguchi method
Taguchi methods
Project scheduling
Robust optimization
Material procurement
Taguchi method
ISSN:0360-8352, 1879-0550
Online Access:Get full text
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Summary:•A bi-objective model for simultaneous project scheduling and material procurement.•Addressing both project schedule and total costs robustness.•Possibility to procure materials from varied suppliers with discount utilization.•Application of tuned meta-heuristics to solve the model of different sizes. Simultaneous planning of project scheduling and material procurement can lead to the project execution costs improvement. Hence, the issue has been addressed in this paper by a robust mixed-integer programming mathematical model, which aims to minimize the corresponding costs and maximize the schedule robustness. The given approach is able to control the degree of solution conservatism, in regard to probabilistic bounds on constraint violation. The proposed model takes the uncertainty issue into account from both viewpoints of activities duration time and execution costs. The NSGA-II and a modified version of multi-objective differential evolution algorithm have been applied as the solution methodologies. Moreover, the principal factors are calibrated by the Taguchi method to provide robustness to the obtained results. Finally, the performance of the solution methods is compared according to a varied set of instances to test their applicability and efficiency.
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ISSN:0360-8352
1879-0550
DOI:10.1016/j.cie.2016.05.017