Title :
Grammatical rules for the automated construction of heuristics
Author :
Terrazas, Germán ; Krasnogor, Natalio
Author_Institution :
ASAP Group, Univ. of Nottingham, Nottingham, UK
Abstract :
Developing a problem-domain independent methodology to automatically generate high performing solving strategies for specific problems is one of the challenging trends on hyper-heuristics design. Designing hyper-heuristics is important because they raise the level of generality on automated problem solving by attempting to select and/or generate tailored heuristics for the problem at hand. In this paper, we present a three-steps methodology that combines multiple sequence alignment and grammatical induction in order to automatically generate high performing solving strategies for a combinatorial optimisation problem. We present proof-of-concept results of applying this methodology to instances of the well-known symmetric TSP. The goal here is to demonstrate feasibility rather than compete with state of the art TSP solvers. This TSP is chosen only because it is an easy to state and well known problem.
Keywords :
inference mechanisms; problem solving; travelling salesman problems; automated problem solving; combinatorial optimisation; grammatical induction; grammatical rules; hyper-heuristics design; multiple sequence alignment; problem-domain independent methodology; symmetric TSP; travelling salesman problem; Construction industry; Encoding; Grammar; Heuristic algorithms; Optimization; Search problems; Training;
Conference_Titel :
Evolutionary Computation (CEC), 2010 IEEE Congress on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6909-3
DOI :
10.1109/CEC.2010.5586192