Analyzing the landscape of a graph based hyper-heuristic for timetabling problems

Hyper-heuristics can be thought of as “heuristics to choose heuristics”. They are concerned with adaptively finding solution methods, rather than directly producing a solution for the particular problem at hand. Hence, an important feature of hyper-heuristics is that they operate on a search space of heuristics rather than directly on a search space of problem solutions. A motivating aim is to build systems which are fundamentally more generic than is possible today. Understanding the structure of these heuristic search spaces is therefore, a research direction worth exploring. In this paper, we use the notion of fitness landscapes in the context of constructive hyper-heuristics. We conduct a landscape analysis on a heuristic search space conformed by sequences of graph coloring heuristics for timetabling. Our study reveals that these landscapes have a high level of neutrality and positional bias. Furthermore, although rugged, they have the encouraging feature of a globally conv...

• Type: Conference
• Year: 2009
• Where: GECCO
• Authors: Gabriela Ochoa, Rong Qu, Edmund K. Burke
• Keywords: Artificial Intelligence, GECCO 2009, Heuristic Search Space, Heuristics, Search Space