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Automating the Generation of VNS Components with Grammatical Evolution
| Citations: | 3 - 0 self |
BibTeX
@MISC{Özcan_automatingthe,
author = {Ender Özcan and John Drake and Nikolaos Kililis},
title = {Automating the Generation of VNS Components with Grammatical Evolution},
year = {}
}
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Abstract
Abstract. The vehicle routing problem (VRP) is a family of problems whereby a fleet of vehicles must service the commodity demands of a set of geographically scattered customers from one or more depots, subject to a number of constraints. Early hyper-heuristic research focussed on selecting and applying a low-level heuristic at a given stage of an optimisation process. Recent trends have led to a number of approaches being developed to automatically generate heuristics for a number of combinatorial optimisation problems. Previous work on the VRP has shown that the application of hyper-heuristic approaches can yield successful results. In this paper we investigate the potential of grammatical evolution as a method to evolve the components of a variable neighbourhood search (VNS) framework. In particular two components are generated; constructive heuristics to create initial solutions and neighbourhood move operators to change the state of a given solution. The proposed method is tested on standard benchmark instances of two common VRP variants. 1
Keyphrases
grammatical evolution vns component previous work successful result initial solution optimisation process standard benchmark instance combinatorial optimisation problem recent trend variable neighbourhood search commodity demand constructive heuristic hyper-heuristic approach neighbourhood move operator common vrp variant low-level heuristic early hyper-heuristic research
