A multi-objective window optimisation problem

Authors:
Alexander E.I. Brownlee;Jonathan A. Wright;Monjur M. Mourshed
Affiliations:
Loughborough University, Loughborough, United Kingdom;Loughborough University, Loughborough, United Kingdom;Loughborough University, Loughborough, United Kingdom
Venue:
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Year:
2011

Citing 5
Cited 0

Multi-Objective Optimization Using Evolutionary Algorithms

Multi-Objective Optimization Using Evolutionary Algorithms
Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy

Evolutionary Computation
Efficient Linkage Discovery by Limited Probing

Evolutionary Computation
MOCell: A cellular genetic algorithm for multiobjective optimization

International Journal of Intelligent Systems - Special Issue on Nature Inspired Cooperative Strategies for Optimization
A fast and elitist multiobjective genetic algorithm: NSGA-II

IEEE Transactions on Evolutionary Computation

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present an optimisation problem which seeks to locate the Pareto-optimal front of building window and shading designs minimising two objectives: projected energy use of the operational building and its construction cost. This problem is of particular interest because it has many variable interactions and each function evaluation is relatively time-consuming. It also makes use of a freely-available building simulation program EnergyPlus which may be used in many other building design optimisation problems. We describe the problem and report the results of experiments comparing the performance of a number of existing multi-objective evolutionary algorithms applied to it. We conclude that this represents a promising real-world application area.