Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 263171
Loughborough University

Loughborough University Institutional Repository

Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/9713

Title: Phi-array: a novel method for fitness visualization and decision making in evolutionary design optimization
Authors: Mourshed, Monjur
Shikder, Shariful H.
Price, Andrew D.F.
Keywords: Evolutionary optimization
Fitness visualization
Design exploration
Decision making
Artificial lighting
Issue Date: 2011
Publisher: © Elsevier
Citation: MOURSHED, M., SHIKDER, S. and PRICE, A.D.F., 2011. Phi-array: a novel method for fitness visualization and decision making in evolutionary design optimization. Advanced Engineering Informatics, 25 (4), pp. 676 - 687
Abstract: There is a growing interest in integrating model based evolutionary optimization in engineering design decision making for effective search of the solution space. Most applications of evolutionary optimization are concerned with the search for optimal solutions satisfying pre-defined constraints while minimizing or maximizing desired goals. A few have explored post-optimization decision making using concepts such as Pareto optimality, but mostly in multi-objective problems. Sub-optimal solutions are usually discarded and do not contribute to decision making after optimization runs. However, the discarded ‘inferior’ solutions and their fitness contain useful information about underlying sensitivities of the system and can play an important role in creative decision making. The need for understanding the underlying system behavior is more pronounced in cases where variations in the genotype space can cause non-deterministic changes in either the fitness or phenotype space and where fitness evaluations are computationally expensive. The optimized design of an artificial lighting environment of a senior living room is used as a test case to demonstrate the need for and application of fitness visualization in genotype and phenotype spaces for effective decision making. Sub-optimal solutions are retained during optimization and visualized along with the optimum solution in a fitness array visualization system called phi-array, developed as part of this research. The optimization environment is based on genetic algorithm (GA) in which a compute-intensive raytracing rendering engine, RADIANCE, is used to evaluate the fitness of prospective design solutions. Apart from describing the development of the optimization system and demonstrating the utility of phi-array in effective decision making, this article explores optimization parameters and their effectiveness for artificial lighting design problems and the nature of their rugged fitness and constraint landscapes.
Description: This article was published in the journal, Advanced Engineering Informatics [© Elsevier] and the definitive version is available at: http://dx.doi.org/10.1016/j.aei.2011.07.005
Version: Accepted for publication
DOI: 10.1016/j.aei.2011.07.005
URI: https://dspace.lboro.ac.uk/2134/9713
Publisher Link: http://dx.doi.org/10.1016/j.aei.2011.07.005
ISSN: 1474-0346
Appears in Collections:Published Articles (Architecture, Building and Civil Engineering)

Files associated with this item:

File Description SizeFormat
Mourshed-novel-method.pdf5.61 MBAdobe PDFView/Open


SFX Query

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.