Thesis-2008-Yang.pdf (7.46 MB)
Collaborative optimisation in building design with a Pareto-based genetic algorithm
thesis
posted on 2018-09-21, 11:11 authored by Fan YangLarge-scale building design is a constantly evolving discipline. Design managers are
consistently trying to identify means for producing a better product in a shorter
period of time. Hence there is a need for design assistant tools that can help designers
understand the big picture. It is becoming hard to improve the system performance of
building design based merely on advances in individual disciplines. In other words,
improvements in individual disciplines alone are not sufficient to affect the
improvements in the whole system. To achieve higher quality, system-orientated,
holistic, multidisciplinary approaches to building design are needed (NSF, 1996). For
this reason, this research investigates the applicability of multidisciplinary
disciplinary optimisation (MDO) methodology in building design. The MDO methods
divide a single system into a group of smaller sub-systems and effectively manage
interactions between sub-systems. In the context of building design, the single system
refers to the whole building design, and sub-system could be each disciplinary design.
Such approaches could reduce the time and cost associated with the multidisciplinary
design cycle.
This thesis describes the work of developing collaborative optimisation framework
with a Pareto based genetic algorithm (COPGA). [Continues.]
History
School
- Architecture, Building and Civil Engineering
Publisher
© Fan YangPublisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Publication date
2008Notes
A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy at Loughborough University.Language
- en