On Searching A-ary Hypercubes and Related Graphs

Joseph Culberson and Jonathan Lichtner

Foundations of Genetic Algorithms IV, pp263-290, 1996

Abstract

This paper develops two themes on landscapes in search algorithms. First it focuses on the notion of landscapes as being induced by operators and fitness functions together with a frequently overlooked influence, the way in which the operator is used within the algorithm. This latter influence is sometimes confused by the tendency to consider a landscape as representative of a search even when a different operator is introduced into the search. We make a finer distinction and show that even when the graph is strictly adhered to by the operators, functions can be found that exponentially differentiate between algorithms that use the neighbor generation in elitist, non-elitist, full neighbor search and neighborhood sampling techniques. These results can be seen as a form of ``no free lunch'' in that in order to fully analyze an algorithm, no detail can be excluded from the analysis.

The second theme tries to abstract out salient properties of landscapes that are dependent on properties of graphs such as degree, diameter and independent set structure. These properties limit the effects of adversaries in various ways. For this to make sense, we must give up the notion of universal problem solvers, and consider more restricted adversaries that better reflect our expectations of search on specific problem classes. This analysis is mostly restricted to graphs induced by simple operations on sets of strings over fixed alphabets.

Full paper

joe@cs.ualberta.ca