Hemmi_Thesis0219_Redacted.pdf (11.49 MB)

Modelling and Solving Techniques for Stochastic Combinatorial Optimisation Problems

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thesis
posted on 26.02.2019, 04:24 by DAVID HEMMI
Decision making under uncertainty is an important topic in many Industries, such as telecommunication, logistics and energy management. For example, scheduling electricity generators in light of demand and production uncertainties is almost impossible without the help of computers. We tackle such decision problems using a two-step approach. First, we write a model of the problem using mathematics, and secondly, we deploy appropriate algorithms to find a solution to the problem. The contribution of this thesis is two-fold, first we propose techniques to improve mathematical models, and secondly, we present algorithmic innovations to find high quality solutions quickly.

History

Principal supervisor

Guido Tack

Additional supervisor 1

Mark Wallace

Year of Award

2019

Department, School or Centre

Caulfield School of IT

Course

Doctor of Philosophy

Degree Type

DOCTORATE

Faculty

Faculty of Information Technology

Exports

Exports