Anvari, B;
Angeloudis, P;
Ochieng, WY;
(2016)
A multi-objective GA-based optimisation for holistic Manufacturing, transportation and Assembly of precast construction.
Automation in Construction
, 71
(Part 2)
pp. 226-241.
10.1016/j.autcon.2016.08.007.
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Abstract
Resource scheduling of construction proposals allows project managers to assess resource requirements, provide costs and analyse potential delays. The Manufacturing, transportation and Assembly (MtA) sectors of precast construction projects are strongly linked, but considered separately during the scheduling phase. However, it is important to evaluate the cost and time impacts of consequential decisions from manufacturing up to assembly. In this paper, a multi-objective Genetic Algorithm-based (GA-based) searching technique is proposed to solve unified MtA resource scheduling problems (which are equivalent to extended Flexible Job Shop Scheduling Problems). To the best of the authors' knowledge, this is the first time that a GA-based optimisation approach is applied to a holistic MtA problem with the aim of minimising time and cost while maximising safety. The model is evaluated and compared to other exact and non-exact models using instances from the literature and scenarios inspired from real precast constructions.
Type: | Article |
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Title: | A multi-objective GA-based optimisation for holistic Manufacturing, transportation and Assembly of precast construction |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1016/j.autcon.2016.08.007 |
Publisher version: | http://dx.doi.org/10.1016/j.autcon.2016.08.007 |
Language: | English |
Additional information: | This is an article published under a Creative Commons licence Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) https://creativecommons.org/licenses/by-nc-nd/4.0/ |
Keywords: | Science & Technology, Technology, Construction & Building Technology, Engineering, Civil, Engineering, Extended flexible job shop modelling, Genetic algorithm, Precast construction, SHOP SCHEDULING PROBLEMS, GENETIC ALGORITHM, BOUND ALGORITHM, OPERATIONS, SETUP, MODEL |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng |
URI: | https://discovery.ucl.ac.uk/id/eprint/10042204 |
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