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Phi-array: a novel method for fitness visualization and decision making in evolutionary design optimization

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journal contribution
posted on 2012-04-20, 11:06 authored by Monjur Mourshed, Shariful H. Shikder, Andrew Price
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.

History

School

  • Architecture, Building and Civil Engineering

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

Publisher

© Elsevier

Version

  • AM (Accepted Manuscript)

Publication date

2011

Notes

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

ISSN

1474-0346

Language

  • en