Fitness landscape analysis and visualisation can provide significant insights into problem instances and algorithm behaviour. The aim of the workshop is to encourage and promote the use of landscape analysis to improve search algorithms and their understanding. Examples include landscape analysis as a tool to inform the design of algorithms, landscape metrics for online adaptation of search strategies, mining landscape information to predict instance hardness and algorithm runtime. The workshop seeks to bring together researchers interested in landscape analysis and in exploiting problem structure to develop informed search strategies. The workshop provides a unique opportunity to present existing work, propose new ideas or put forward position statements.
Relevant topics include, but are not limited to:
Evolvability and searchability characterisation
Exploiting problem structure
Exploratory landscape analysis
Fitness landscape analysis
Fitness landscape visualisation
Fitness landscape theory
Grey-box optimisation
Informed search strategies
Local optima networks
Multi-objective fitness landscapes
Performance and failure prediction
Workshop date: 17 September 2016
Time: 11:00 — 17:15
Location: Prestonfield Room, John McIntyre Conference Centre
11:00 – 12:30 — 1st Session
The Global Structure of TSP Fitness Landscapes
Gabriela Ochoa, Nadarajen Veerapen
Mk Landscapes Problem Structure
Darrell Whitley, Francisco Chicano, and Brian Goldman
Fitness Landscape Analysis of a Class of NP-Complete Binary Packing Problems
Khulood Alyahya and Jonathan E. Rowe
Fitness Landscape Analysis, Problems Features and Performance Prediction for Multi-objective Optimization
Fabio Daolio, Arnaud Liefooghe, Sébastien Verel, Hernan Aguirre, and Kiyoshi Tanaka
12:30 – 14:00 — Lunch
14:00 – 15:30 — 2nd Session
Fitness Landscape of the Triangle Program
William B. Langdon and Mark Harman
Climbing Fitness Landscapes with the Maximum Expansion Pivoting Rule
Sara Tari, Matthieu Basseur, and Adrien Goëffon
Dynamic Selection of Evolutionary Operators Based on Online Learning and Fitness Landscape Analysis
Pietro A. Consoli, Yi Mei, Leandro L. Minku, and Xin Yao
A Triple Interpretation of Combinatorial Search Spaces
Valentino Santucci and Alfredo Milani
15:30 – 15:45 — Coffee break
15:45 – 17:15 — 3rd Session
Towards Algorithm Portfolio Based on Local Optima Network Features
Sébastien Verel, Fabio Daolio, Gabriela Ochoa, and Marco Tomassini
Exploratory Landscape Analysis By Using the R-Package flacco
Pascal Kerschke and Heike Trautmann
DISCUSSION
Nadarajen Veerapen and Gabriela Ochoa
Computing Science and Mathematics, School of Natural Sciences, University of Stirling, Stirling, FK9 4LA, Scotland.
email: {nve,goc}@cs.stir.ac.uk