Genetic Programming over Context-Free Languages with Linear Constraints for the Knapsack Problem: First Results

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@Article{bruhn:2002:ECJ,

• author = "Peter Bruhn and Andreas Geyer-Schulz",
• title = "Genetic Programming over Context-Free Languages with Linear Constraints for the Knapsack Problem: First Results",
• journal = "Evolutionary Computation",
• year = "2002",
• volume = "10",
• number = "1",
• pages = "51--74",
• month = "Spring",
• keywords = "genetic algorithms, genetic programming, grammatical evolution, grammar-based genetic, programming, combinatorial, optimization, context-free grammars, with linear constraints, knapsack problems",
• broken = "http://www.ingentaconnect.com/content/mitpress/evco/2002/00000010/00000001/art00004",
• DOI = "doi:10.1162/106365602317301772",
• abstract = "we introduce genetic programming over context-free languages with linear constraints for combinatorial optimization, apply this method to several variants of the multidimensional knapsack problem, and discuss its performance relative to Michalewicz's genetic algorithm with penalty functions. With respect to Michalewicz's approach, we demonstrate that genetic programming over context-free languages with linear constraints improves convergence. A final result is that genetic programming over context-free languages with linear constraints is ideally suited to modeling complementarities between items in a knapsack problem: The more complementarities in the problem, the stronger the performance in comparison to its competitors.",

}

Genetic Programming entries for Peter Bruhn Andreas Geyer-Schulz

Citations