Tutorial: Evolutionary Algorithms and Hyper-Heuristics

Hyper-heuristics is a rapidly developing domain which has proven to be
effective at providing generalized solutions to problems and across
problem domains. Evolutionary algorithms have played a pivotal role in
the advancement of hyper-heuristics, especially generation
hyper-heuristics. Evolutionary algorithm hyper-heuristics have been
successful applied to solving problems in various domains including
packing problems, educational timetabling, vehicle routing,
permutation flowshop and financial forecasting amongst others. The aim
of the tutorial is to firstly provide an introduction to evolutionary
algorithm hyper-heuristics for researchers interested in working in
this domain. An overview of hyper-heuristics will be provided
including the assessment of hyper-heuristic performance. The tutorial
will examine each of the four categories of hyper-heuristics, namely,
selection constructive, selection perturbative, generation
constructive and generation perturbative, showing how evolutionary
algorithms can be used for each type of hyper-heuristic. A case study
will be presented for each type of hyper-heuristic to provide
researchers with a foundation to start their own research in this
area. The EvoHyp library will be used to demonstrate the
implementation of a genetic algorithm hyper-heuristic for the case
studies for selection hyper-heuristics and a genetic programming
hyper-heuristic for the generation hyper-heuristics. A theoretical
understanding of evolutionary algorithm hyper-heuristics will be
provided. Challenges in the implementation of evolutionary algorithm
hyper-heuristics will be highlighted. An emerging research direction
is using hyper-heuristics for the automated design of computational
intelligence techniques. The tutorial will look at the synergistic
relationship between evolutionary algorithms and hyper-heuristics in
this area. The use of hyper-heuristics for the automated design of
evolutionary algorithms will be examined as well as the application of
evolutionary algorithm hyper-heuristics for the design of
computational intelligence techniques. The tutorial will end with a
discussion session on future directions in evolutionary algorithms and
hyper-heuristics.