An Attribute Grammar Decoder for the 01 MultiConstrained Knapsack Problem

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.

• Type: Conference
• Year: 2005
• Where: EVOW
• Authors: Robert Cleary, Michael O'Neill
• Keywords: Artificial Intelligence, Attribute Grammar Specification, Attribute Grammars, EVOW 2005, Grammar Allows Ge