Design Buildings Optimally: A Lifecycle Assessment Approach

Ossama Hosny, Ahmed Elhakeem

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper structures a generic framework to support optimum design for multi-buildings in desert environment. The framework is targeting an environmental friendly design with minimum lifecycle cost, using Genetic Algorithms (Gas). GAs function through a set of success measures which evaluates the design, formulates a proper objective, and reflects possible tangible/intangible constraints. The framework optimizes the design and categorizes it under a certain environmental category at minimum Life Cycle Cost (LCC). It consists of three main modules: (1) a custom Building InformationModel (BIM) for desert buildings with a compatibility checker as a central interactive database; (2) a system evaluator module to evaluate the proposed success measures for the design; and (3) a GAs optimization module to ensure optimum design. The framework functions through three levels: the building components, integrated building, and multi-building levels. At the component level the design team should be able to select components in a designed sequence to ensure compatibility among various components, while at the building level; the team can relatively locate and orient each individual building. Finally, at the multi-building (compound) level the whole design can be evaluated using success measures of natural light, site capacity, shading impact on natural lighting, thermal change, visual access and energy saving. The framework through genetic algorithms optimizes the design by determining proper types of building components and relative buildings locations and orientations which ensure categorizing the design under a specific category or meet certain preferences at minimum lifecycle cost.
Original languageEnglish (US)
Title of host publicationProceedings of the New Developments in Structural Engineering and Construction
PublisherResearch Publishing Services
ISBN (Print)9789810753542
StatePublished - 2013
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUK-C1-014-12
Acknowledgements: This publication is based on the work supported by Award No. KUK-C1-014-12, made by King Abdullah University of Science and Technology (KAUST), Saudi Arabia.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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