- author = "Mohammad M. O. Gholami and Brian J. Ross",
- title = "Passive solar building design using genetic programming",
- booktitle = "GECCO '14: Proceedings of the 2014 conference on Genetic and evolutionary computation",
- year = "2014",
- editor = "Christian Igel and Dirk V. Arnold and Christian Gagne and Elena Popovici and Anne Auger and Jaume Bacardit and Dimo Brockhoff and Stefano Cagnoni and Kalyanmoy Deb and Benjamin Doerr and James Foster and Tobias Glasmachers and Emma Hart and Malcolm I. Heywood and Hitoshi Iba and Christian Jacob and Thomas Jansen and Yaochu Jin and Marouane Kessentini and Joshua D. Knowles and William B. Langdon and Pedro Larranaga and Sean Luke and Gabriel Luque and John A. W. McCall and Marco A. {Montes de Oca} and Alison Motsinger-Reif and Yew Soon Ong and Michael Palmer and Konstantinos E. Parsopoulos and Guenther Raidl and Sebastian Risi and Guenther Ruhe and Tom Schaul and Thomas Schmickl and Bernhard Sendhoff and Kenneth O. Stanley and Thomas Stuetzle and Dirk Thierens and Julian Togelius and Carsten Witt and Christine Zarges",
- isbn13 = "978-1-4503-2662-9",
- pages = "1111--1118",
- keywords = "genetic algorithms, genetic programming",
- month = "12-16 " # jul,
- organisation = "SIGEVO",
- address = "Vancouver, BC, Canada",
-
URL = "
http://doi.acm.org/10.1145/2576768.2598211",
-
DOI = "
doi:10.1145/2576768.2598211",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
- abstract = "Passive solar building design considers the effect that sunlight has on energy usage. The goal is to reduce the need for artificial cooling and heating devices, thereby saving energy costs. A number of competing design objectives can arise. Window heat gain during winter requires large windows. These same windows, however, reduce energy efficiency during nights and summers. Other model requirements add further complications, which creates a challenging optimisation problem. We use genetic programming for passive solar building design. The EnergyPlus system is used to evaluate energy consumption. It considers factors ranging from model construction (shape, windows, materials) to location particulars (latitude/longitude, weather, time of day/year). We use a strongly typed design language to build 3D models, and multi-objective fitness to evaluate the multiple design objectives. Experimental results showed that balancing window heat gain and total energy use is challenging, although our multi-objective strategy could find interesting compromises. Many factors (roof shape, material selection) were consistently optimised by evolution. We also found that geographic aspects of the location play a critical role in the final building design.",
-
notes = "See also Brock University technical report CS-14-02
Jan 2014.
Also known as \cite{2598211} GECCO-2014 A joint meeting of the twenty third international conference on genetic algorithms (ICGA-2014) and the nineteenth annual genetic programming conference (GP-2014)",
