School of Computer Science and Software Engineering

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Lucas Bradstreet

Phone: (+61 8) 6488 1945
Fax: (+61 8) 6488 1089


Start date

Submission date

Lucas Bradstreet

Thesis

Transformation of Multi-objective Optimisation Problems to Single Objective Problems via Hypervolume

Summary

Multi-objective evolutionary algorithms (MOEAs) are an important new field. MOEAs are used for optimisation problems where trade-offs between multiple objectives may be required and where trade-offs cannot be predicted in advance, where trade-offs change over time (e.g. depending on market conditions), or where "engineering judgement" is required to make the optimal design decision. Cases where MOEAs have been applied successfully to real world problems include Barone's rock crusher MOEA and network layout problems.

There are many issues encountered when using MOEAs, such as good methods for diversity maintenance. Given the many applications of MOEAs to many current problems and the immaturity of the field, it is a fertile field for research into techniques which allow them to operate more efficiently and effectively.

Why my research is important

Given the many applications of MOEAs to many current problems and the immaturity of the field, it is a fertile field for research into techniques which allow them to operate more efficiently and effectively.


 

School of Computer Science and Software Engineering

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Last updated:
Wednesday, 13 February, 2013 8:19 AM

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