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2021 | OriginalPaper | Chapter

Multi-objective Workforce Allocation in Construction Projects

Authors : Andrew Iskandar, Richard Allmendinger

Published in: Applications of Evolutionary Computation

Publisher: Springer International Publishing

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Abstract

Managing construction projects is a complex, resource-intense and risky task that involves the organization and management of people skilled in the design and completion of construction projects. Embarking on a construction project means to plan the allocation of resources and labour, while ensuring that the output (e.g. a new building) meets a certain quality, and is delivered in time and within budget without breaching contractual obligations. We formulate a simplified version of this task as a constrained multi-objective optimization problem, and then use a non-dominated sorting genetic algorithm to tackle the problem. In addition to providing a formal definition of the problem, further contributions of this work include the validation of the methodology using real data of construction projects varying in scale and resource-utilisation; the use of real data is scarce in the construction project management area. We also perform a scenario-based analysis to understand how the approach reacts to changing environmental parameters (such as availability of resources). Finally, we discuss practical implications. Our empirical analysis highlights that the proposed approach improves significantly in terms of project budget, quality, and duration targets, when compared with the industry standard.
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Metadata
Title
Multi-objective Workforce Allocation in Construction Projects
Authors
Andrew Iskandar
Richard Allmendinger
Copyright Year
2021
Book
Applications of Evolutionary Computation

Print ISBN: 978-3-030-72698-0

Electronic ISBN: 978-3-030-72699-7

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-72699-7_4