<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">Jonathan A. Wright</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A comparison of deterministic and probabilistic optimization algorithms for nonsmooth simulation-based optimization </style></title><secondary-title><style face="normal" font="default" size="100%">Building and Environment</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">coordinate search</style></keyword><keyword><style  face="normal" font="default" size="100%">direct search</style></keyword><keyword><style  face="normal" font="default" size="100%">genetic algorithm</style></keyword><keyword><style  face="normal" font="default" size="100%">hooke–jeeves</style></keyword><keyword><style  face="normal" font="default" size="100%">optimization</style></keyword><keyword><style  face="normal" font="default" size="100%">particle swarm optimization</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2004</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">39</style></volume><pages><style face="normal" font="default" size="100%">989-999</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In solving optimization problems for building design and control, the cost function is often evaluated using a detailed building simulation program. These programs contain code features that cause the cost function to be discontinuous. Optimization algorithms that require smoothness can fail on such problems. Evaluating the cost function is often so time-consuming that stochastic optimization algorithms are run using only a few simulations, which decreases the probability of getting close to a minimum. To show how applicable direct search, stochastic, and gradient-based optimization algorithms are for solving such optimization problems, we compare the performance of these algorithms in minimizing cost functions with different smoothness. We also explain what causes the large discontinuities in the cost functions.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">8</style></issue><section><style face="normal" font="default" size="100%">989</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">Jonathan A. Wright</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Godfried Augenbroe</style></author><author><style face="normal" font="default" size="100%">Jan Hensen</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Comparison of a generalized pattern search and a genetic algorithm optimization method</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. of the 8th IBPSA Conference</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ibpsa.org/proceedings/BS2003/BS03_1401_1408.pdf</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Eindhoven, Netherlands</style></pub-location><volume><style face="normal" font="default" size="100%">III</style></volume><pages><style face="normal" font="default" size="100%">1401-1408</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Building and HVAC system design can significantly improve if numerical optimization is used. However, if a cost function that is smooth in the design parameter is evaluated by a building energy simulation program, it usually becomes replaced with a numerical approximation that is discontinuous in the design parameter. Moreover, many building simulation programs do not allow obtaining an error bound for the numerical approximations to the cost function. Thus, if a cost function is evaluated by such a program, optimization algorithms that depend on smoothness of the cost function can fail far from a minimum.&lt;/p&gt;&lt;p&gt;For such problems it is unclear how the Hooke-Jeeves Generalized Pattern Search optimization algorithm and the simple Genetic Algorithm perform. The Hooke-Jeeves algorithm depends on smoothness of the cost function, whereas the simple Genetic Algorithm may not even converge if the cost function is smooth. Therefore, we are interested in how these algorithms perform if used in conjunction with a cost function evaluated by a building energy simulation program.&lt;/p&gt;&lt;p&gt;In this paper we show what can be expected from the two algorithms and compare their performance in minimizing the annual primary energy consumption of an office building in three locations. The problem has 13 design parameters and the cost function has large discontinuities. The optimization algorithms reduce the energy consumption by 7% to 32%, depending on the building location. Given the short labor time to set up the optimization problems, such reductions can yield considerable economic gains.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Richard A. Buswell</style></author><author><style face="normal" font="default" size="100%">Philip Haves</style></author><author><style face="normal" font="default" size="100%">Jonathan A. Wright</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Field Testing Model-Based Condition Monitoring on a HVAC Cooling Coil Sub-System</style></title><secondary-title><style face="normal" font="default" size="100%">Building Services Engineering Research &amp; Technology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><volume><style face="normal" font="default" size="100%">24</style></volume><pages><style face="normal" font="default" size="100%">103-116</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">2</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Richard A. 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Wright</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Non-Linear Recursive Parameter Estimation Applied to Fault Detection and Diagnosis in Real Buildings</style></title><secondary-title><style face="normal" font="default" size="100%">System Simulation in Buildings ’02</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2002</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Liège, Belgium</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Philip Haves</style></author><author><style face="normal" font="default" size="100%">Tim I. Salsbury</style></author><author><style face="normal" font="default" size="100%">Jonathan A. Wright</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Condition Monitoring in HVAC Subsystems using First Principles Models</style></title><secondary-title><style face="normal" font="default" size="100%">ASHRAE Transactions</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1996</style></year></dates><volume><style face="normal" font="default" size="100%">102</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">Pt. 1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tim I. Salsbury</style></author><author><style face="normal" font="default" size="100%">Philip Haves</style></author><author><style face="normal" font="default" size="100%">Jonathan A. Wright</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Fault Detection and Diagnosis Method Based on First Principles Models and Expert Rules</style></title><secondary-title><style face="normal" font="default" size="100%">Tsinghua HVAC-95</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1995</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/1995</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Bejing, China</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mourad Benouarets</style></author><author><style face="normal" font="default" size="100%">Arthur L. Dexter</style></author><author><style face="normal" font="default" size="100%">Richard S. Fargus</style></author><author><style face="normal" font="default" size="100%">Philip Haves</style></author><author><style face="normal" font="default" size="100%">Tim I. Salsbury</style></author><author><style face="normal" font="default" size="100%">Jonathan A. Wright</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Model-Based Approaches to Fault Detection and Diagnosis in Air-Conditioning System</style></title><secondary-title><style face="normal" font="default" size="100%">System Simulation in Buildings &#039;94</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1994</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/1994</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Liège, Belgium</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record></records></xml>