Abstract
AbstractIn this paper, we introduce a new approach to genotype-phenotype mapping for Grammatical Evolution (GE) using an attribute grammar (AG) to solve 0-1 multiconstraint knapsack problems.Previous work on AGs dealt with constraint violations through repeated remapping of non-terminals, which generated many introns, thus decreasing the power of the evolutionary search.Our approach incorporates a form of lookahead into the mapping process using AG to focus only on feasible solutions and so avoid repeated remapping and introns. The results presented in this paper show that the proposed approach is capable of obtaining high quality solutions for the tested problem instances using fewer evaluations than existing methods.KeywordsProblem InstanceKnapsack ProblemConstraint Satisfaction ProblemConstraint ViolationSemantic FunctionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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