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A tabu search approach to automated map generalisation


J. Mark Ware, Ian D. Wilson, J. Andrew Ware, and Christopher B. Jones

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Abstract

Displaying map data at scales smaller than its source can result in objects that are either too small to be seen or too close to each other to be distinguishable. Furthermore, graphic conflicts become more likely when certain map symbols are no longer a true scale representation of the feature they represent. Map generalisation includes the processes by which such conflicts are resolved. The map generalisation technique presented here is exponential in the problem size and is, as such, combinatorially large (NP-hard). We show how the tabu search metaheuristic was used to resolve spatial conflict between objects after scaling, achieving near optimal solutions within practical time constraints.


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