Methods for reducing search and evaluating fitness functions in genetic algorithms for the Snake-in-the-Box problem

Abstract

This thesis explores the use of Genetic Algorithms in approaching the Snake-In-The-Box problem in dimension 8. It discusses methods for improving the solutions found by reducing the representation space for the problem. It presents a representation scheme called Frequency-Based Transition Reassignment (FBTR), which creates a unified interpretation of individuals to prune the search space. FBTR is compared to a standard transition-based representation to determine its effectiveness. It is also compared to a canonical representation that was presented by K. J. Kochut in 1996 which is a different technique meant to reduce the search space. In addition, this thesis introduces the concept of a snake blocker and identifies methods for dealing with snake blockers. These methods are evaluated for their impact on the GA as a whole. Furthermore, fitness functions are explored in great detail and a variety of components to supplement the length of the longest snake in the chromosome, are suggested and evaluated.