%0 Journal Article %1 bruhn:2002:ECJ %A Bruhn, Peter %A Geyer-Schulz, Andreas %D 2002 %J Evolutionary Computation %K algorithms, combinatorial, constraints, context-free evolution, genetic genetic, grammar-based grammars, grammatical knapsack linear optimization, problems programming, with %N 1 %P 51--74 %R doi:10.1162/106365602317301772 %T Genetic Programming over Context-Free Languages with Linear Constraints for the Knapsack Problem: First Results %U http://www.ingentaconnect.com/content/mitpress/evco/2002/00000010/00000001/art00004 %V 10 %X 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.

@article{bruhn:2002:ECJ, 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.}, added-at = {2008-06-19T17:35:00.000+0200}, author = {Bruhn, Peter and Geyer-Schulz, Andreas}, biburl = {https://www.bibsonomy.org/bibtex/2d0ab02e7c76165958bd68ede62d3f4d8/brazovayeye}, doi = {doi:10.1162/106365602317301772}, interhash = {4b30bce74b17322ccd0d20df09b11204}, intrahash = {d0ab02e7c76165958bd68ede62d3f4d8}, journal = {Evolutionary Computation}, keywords = {algorithms, combinatorial, constraints, context-free evolution, genetic genetic, grammar-based grammars, grammatical knapsack linear optimization, problems programming, with}, month = {Spring}, number = 1, pages = {51--74}, timestamp = {2008-06-19T17:37:04.000+0200}, title = {Genetic Programming over Context-Free Languages with Linear Constraints for the Knapsack Problem: First Results}, url = {http://www.ingentaconnect.com/content/mitpress/evco/2002/00000010/00000001/art00004}, volume = 10, year = 2002 }