Genetic Algorithm–Simulation Framework for Decision Making in Construction Site Layout Planning

RazaviAlavi, SeyedReza and AbouRizk, Simaan (2017) Genetic Algorithm–Simulation Framework for Decision Making in Construction Site Layout Planning. Journal of Construction Engineering and Management, 143 (1). 04016084. ISSN 0733-9364

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Official URL: https://doi.org/10.1061/(asce)co.1943-7862.0001213

Abstract

Site layout planning is a complicated task in many construction projects because of the diversity of decision variables, conflicting objectives, and the variety of possible solutions. This paper describes a framework that facilitates decision making on site-layout planning problems. The framework consists of three phases: (1) functionality evaluation phase (FEP), which qualitatively evaluates using a new method; (2) cost evaluation phase (CEP), which quantitatively evaluates the goodness of the layouts using simulation; and (3) value evaluation phase (VEP), which selects the most desirable layout from both qualitative and quantitative aspects. This framework also takes advantage of heuristic optimization through genetic algorithm (GA) to search for the most qualified layouts within FEP. The primary contribution of this research is to introduce a novel method for evaluating quality of layouts, which more realistically model the closeness constraints, and consider size and location desirability in the evaluating function. Also, using simulation for estimating project cost improves the effectiveness of the framework in practice because simulation can model construction processes, uncertainties, resources, and dynamic interactions between various parameters. Applicability of the framework is demonstrated through a case study of the layout planning of a tunneling project.

Item Type: Article
Subjects: H200 Civil Engineering
H300 Mechanical Engineering
Department: Faculties > Engineering and Environment > Mechanical and Construction Engineering
Depositing User: Elena Carlaw
Date Deposited: 16 Jul 2020 12:45
Last Modified: 16 Jul 2020 12:45
URI: http://nrl.northumbria.ac.uk/id/eprint/43793

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