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ARiSeL, proposed by [Duque_Church2004] , aggregates N areas into P spatially contiguous regions while minimizing intra-regional heterogeneity (measured as the within-cluster sum of squares from each area to the attribute centroid of its cluster). This algorithm is a modification of Openshaw’s AZP-tabu [Openshaw_Rao1995]. In ARISeL the construction of an initial feasible solution is repeated several times (inits) before running Tabu Search algorithm [Glover1977].
In GeoDa, a checkbox "ARiSeL" will be added along with a textctrl that allows users to input the (inits) number of how many constructions (of initial feasible solution) will be re-run. The default value of inits in clusterpy is 5, and we double it to 10 in GeoDa.
When user checks the "ARiSeL" box, the re-run of construction can be applied to AZP Tabu (default), AZP and AZP SA.
The text was updated successfully, but these errors were encountered:
ARiSeL, proposed by [Duque_Church2004] , aggregates N areas into P spatially contiguous regions while minimizing intra-regional heterogeneity (measured as the within-cluster sum of squares from each area to the attribute centroid of its cluster). This algorithm is a modification of Openshaw’s AZP-tabu [Openshaw_Rao1995]. In ARISeL the construction of an initial feasible solution is repeated several times (inits) before running Tabu Search algorithm [Glover1977].
In GeoDa, a checkbox "ARiSeL" will be added along with a textctrl that allows users to input the (inits) number of how many constructions (of initial feasible solution) will be re-run. The default value of inits in clusterpy is 5, and we double it to 10 in GeoDa.
When user checks the "ARiSeL" box, the re-run of construction can be applied to AZP Tabu (default), AZP and AZP SA.
The text was updated successfully, but these errors were encountered: