Early design analysis using optimization techniques in design/practice

2014 ASHRAE/IBPSA-USA Building Simulation Conference

Volumn , Issue , 2014, Pages 284-291

  Singh, Sukreet ^a   Kensek, Karen ^b  

^a Cuningham Group Architecture Inc   (United States)

^b UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SOFTWARE; ENERGY UTILIZATION; GENETIC ALGORITHMS; KNOWLEDGE BASED SYSTEMS; OPTIMIZATION;

DESIGN ALTERNATIVES; ENERGY CONSUMPTION OPTIMIZATION; INTEGRATED DESIGN APPROACHES; OPTIMIZATION ALGORITHMS; OPTIMIZATION TECHNIQUES; PARAMETRIC -ANALYSIS; SIMULATION AND OPTIMIZATION; SIMULATION SOFTWARE;

DESIGN;

EID: 84938887192     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

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2. Ciftcioglu, O'Bittermann, M. 2009. Adaptive formation of Pareto front in evolutionary multi-objective optimization. Delft Tech University, Netherlands.
3. Coello, C.A. et al. 2007. Evolutionary Algorithms for Solving Multi-objective problems, Genetic Evolutionary Computation Series, 2nd ed, NY
4. Haupt, R.L. and Haupt S.E. 2004. Practical genetic algorithms. Hoboken, NJ, John Wiley, pp 97-103
5. Heller, Jonathan et al 2011. Sensitivity Analysis: Comparing the impact of Design, Operation, and Tenant Behavior on Building Energy Performance
6. Miller, Nathan 2011. USC 517 Galapagos Course, http://wiki.theprovingground.org/usc-arch517-galapagos, last accessed February 2014.
7. Sefaira, Realtime Analysis, http://www.sefaira.com/resources/three-simple-steps-to-better-performance, last accessed March 2014.
8. Shi, Xing and Yang, Wenjie. 2013. Performance-driven architectural design and optimization technique from a perspective of architects. Automation in Construction, Vol 32.
9. Wu, Geman, et al. 2012. Studies in Preliminary Design of Fenestration: Balancing daylight harvesting and energy consumption, PLEA 2012, Peru.