Tutorial - Landscape Analysis of Optimisation Problems and Algorithms

Katherine Malan,University of South Africa; Gabriela Ochoa, University of Stirling, UK, ABSTRACT: The notion of a fitness landscape was first introduced in 1932 to understand natural evolution, but the concept was later applied in the context of evolutionary computation to understand algorithm behaviour on different problems. In the last decade, the field of fitness landscapes has experienced a large upswing in research, evident in the increased number of published papers on the topic as well as regular tutorials, workshops and special sessions at all the major evolutionary computation conferences. More recently, landscape analysis has been used in contexts beyond evolutionary computation in areas such as feature selection for data mining, hyperparameter optimisation and neural network training. A further recent advance has been the analysis of landscapes through the trajectories of algorithms. The search paths of algorithms provide samples of the search space that can be seen as a view of the landscape from the perspective of the algorithm. What algorithms \see\" as they move through the search space of different problems can help us understand how evolutionary and other search algorithms behave on problems with different characteristics. This tutorial provides an overview of landscape analysis in different contexts including techniques for understanding and characterising discrete and continuous optimisation problems applications of landscape analysis in performance prediction and algorithm selection and the analysis of search trajectories to understand the behaviour of search algorithms."""