Template-type: ReDif-Paper 1.0
Author-Name: Kolen Antoon 
Author-workplace-name: METEOR
Title: A genetic algorithm for the partial binary constraint satisfaction problem: an application to a frequency assignment problem
Abstract: We describe a genetic algorithm for the partial constraint satisfaction problem. The typical elements of a genetic algorithm, selection, mutation and cross-over, are filled in with combinatorial ideas. For instance, cross-over of two solutions is performed by taking the one or two domain elements in the solutions of each of the variables as the complete domain of the variable. Then a branch-and-bound method is used for solving this small instance. When tested on a class of frequency assignment problems this genetic algorithm produced the best known solutions for all test problems. This feeds the idea that combinatorial ideas may well be useful in genetic algorithms. 
Keywords: Economics ; 
Series: Research Memoranda
Creation-Date: 2006
Number: 045
File-URL: http://digitalarchive.maastrichtuniversity.nl/fedora/objects/guid:0c5da7e2-51fe-423d-9914-839d3ae187a4/datastreams/ASSET1/content
File-Format: application/pdf
File-Size: 133933
Handle: RePEc:unm:umamet:2006045