Grammatical rules for the automated construction of heuristics
18 Jul 2010-pp 1-8
TL;DR: This paper presents 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.
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.
Citations
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01 Jan 2005
TL;DR: Several variants and generalizations of the Or-opt heuristic for the Symmetric Travelling Salesman Problem are developed and compared on random and planar instances to significantly improve upon the standard 2-opt and Or- opt heuristics.
Abstract: Several variants and generalizations of the Or-opt heuristic for the Symmetric Travelling Salesman Problem are developed and compared on random and planar instances. Some of the proposed algorithms are shown to significantly improve upon the standard 2-opt and Or-opt heuristics.
11 citations
References
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01 Jan 2007
TL;DR: It is shown how Lindenmayer's parallel rewriting systems, also known as L-Systems, can be used to encode the instances and the optimal tours of the ETSP and a general framework for the practical issues of the automatic generation of ETSP instances in TSPLIB format is presented.
Abstract: Very recently, four diierent types of instances of the Euclidean Traveling Salesman Problem (ETSP) on the plane have been introduced. The coordinates of the cities have been deened by geometric iterative constructive processes. For each one of these instances, a unique optimal tour through the cities has been provided. Due to the nature of the constructive processes and the induction proofs of optimality, they provide us with a remarkable set of instances of the ETSP with arbitrarily many cities, and with known optimal tours of diierent fractal dimensions. In this paper we show how Lindenmayer's parallel rewriting systems, also known as L-Systems, can be used to encode the instances and the optimal tours. We present a general framework for the practical issues of the automatic generation of ETSP instances in TSPLIB format from L-Systems. no formato TSPLIB.
5 citations
12 Jul 2008
TL;DR: This paper presents a set of experiments on the use of Learning Classifier Systems for the purpose of solving combinatorial optimisation problems and shows that an LCS is capable of learning rules to recognise to which family of instances a set containing a sample of the cities in the problem belongs to and hence automatically select the best heuristic to solve it.
Abstract: This paper presents a set of experiments on the use of Learning Classifier Systems for the purpose of solving combinatorial optimisation problems. We demonstrate our approach with a set of Fractal Travelling Salesman Problem (TSP) instances for which it is possible to know by construction the optimal tour regardless of the number of cities in them. This special type of TSP instances are ideal for testing new methods as they are well characterised in their solvability and easy to use for scalability studies. Our results show that an LCS is capable of learning rules to recognise to which family of instances a set containing a sample of the cities in the problem belongs to and hence automatically select the best heuristic to solve it. Moreover, we have also trained the LCS to recognise links belonging to the optimal tour.
3 citations
"Grammatical rules for the automated..." refers background in this paper
...…of Computer Science, University of Nottingham, UK, email:gzt@cs.nott.ac.uk Natalio Krasnogor, ASAP Group, School of Computer Science, University of Nottingham, UK, email:nxk@cs.nott.ac.uk presented and discussed in Section V. Finally, conclusions and further work are the subject of Section VI....
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01 May 2010
TL;DR: This paper presents an alternative methodology that sheds light on simple methodologies that efficiently cooperate by means of local interactions that are seen as building blocks for the automated manufacture of good performing heuristic search strategies.
Abstract: The current research trends on hyper-heuristics design have sprung up in two different flavours: heuristics that choose heuristics and heuristics that generate heuristics. In the latter, the goal is to develop a problem-domain independent strategy to automatically generate a good performing heuristic for specific problems, that is, the input to the algorithm are problems and the output are problem-tailored heuristics. This can be done, for example, by automatically selecting and combining different low-level heuristics into a problem specific and effective strategy. Thus, hyper-heuristics raise the level of generality on automated problem solving by attempting to select and/or generate tailored heuristics for the problem in hand. Some approaches like genetic programming have been proposed for this. In this paper, we report on an alternative methodology that sheds light on simple methodologies that efficiently cooperate by means of local interactions. These entities are seen as building blocks, the combination of which is employed for the automated manufacture of good performing heuristic search strategies.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.
2 citations
"Grammatical rules for the automated..." refers background or methods in this paper
...Hence, our interest here lays on whether the use of a grammatical induction algorithm would be able to infer a grammar for deriving heuristics that construct high quality solutions when applied to the problem at hand....
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...Another application is reported in [14] where a grammatical inference method is proposed to derive a grammar from a surveillance system....
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...In our previous work [1], we reported on a methodology for the automated manufacture of heuristic search strategies that produces good solutions for a given combinatorial optimisation problem....
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