An attribute grammar decoder for the 01 multiconstrained knapsack problem

  • Authors:
  • Robert Cleary;Michael O’Neill

  • Affiliations:
  • University of Limerick, Ireland;University of Limerick, Ireland

  • Venue:
  • EvoCOP'05 Proceedings of the 5th European conference on Evolutionary Computation in Combinatorial Optimization
  • Year:
  • 2005

Quantified Score

Hi-index 0.00

Visualization

Abstract

We describe how the standard genotype-phenotype mapping process of Grammatical Evolution (GE) can be enhanced with an attribute grammar to allow GE to operate as a decoder-based Evolutionary Algorithm (EA). Use of an attribute grammar allows GE to maintain context-sensitive and semantic information pertinent to the capacity constraints of the 01 Multiconstrained Knapsack Problem (MKP). An attribute grammar specification is used to perform decoding similar to a first-fit heuristic. The results presented are encouraging, demonstrating that GE in conjunction with attribute grammars can provide an improvement over the standard context-free mapping process for problems in this domain.