Linden Hutchinson
Advanced Routing for a Mixed Fleet of Electric Vehicles
We investigate the electric vehicle routing problem, for which our objective is to develop a number of novel effective matheuristics inspired by two promising frameworks capable to explore solution space by learning the problem’s model from selected solutions. The first framework is the Probabilistic Model-Building Evolutionary Approach driven by linkage learning of the behaviour of decision variables in exact solvers. The second framework is the Merge Search that tackles a problem through constructing a simpler but time-efficient ‘merged’ model with aggregated variables, which it solves and alters based on the obtained results and the results of a heuristic search, thus improving the overall search. They both represent the hybridisation of algorithmic techniques from operations research and artificial intelligence and have been proven to be efficient for large-scale discrete optimisation problems. New superior techniques to the benchmark problem should allow us to create later a prototype for our industrial partner and succeed with real-world problems.
Linden Hutchinson
Deakin University
Linden Hutchinson is currently undertaking a Bachelor’s of Artificial Intelligence at Deakin University.
He has worked at a software company for over three years and his interests include spending hours automating tasks that would take 10 minutes to perform manually.
His professional experience has strengthened his programming ability and he’s always on the lookout for ways to optimise his software.
He is interested in pursuing research after completing his undergraduate studies, especially pertaining to practical applications of Artificial Intelligence.
You may be interested in
Sona Reddy
Distribution of Maximal and Minimal Deviation in Multivariate Chebyshev Approximation Problem
