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Heuristic Methods

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Multicriteria Decision Analysis in Geographic Information Science

Part of the book series: Advances in Geographic Information Science ((AGIS))

Abstract

This chapter provides an overview of GIS-based heuristic methods for tackling spatial multiobjective decision problems. The methods are classified into two groups. First, there is a group of basic heuristic methods that tend to be designed for solving specific spatial problems. This group includes methods such as: site suitability heuristics, site location heuristics, and greedy algorithms. Second, there is a large collection of meta-heuristics. These approaches typically employ conventional meta-heuristics for solving spatial optimization problems using GIS. This group of methods include: genetic algorithms, simulated annealing, tabu search, and swarm intelligence methods. This chapter focusses on the concepts and procedures of genetic algorithms.

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  1. Department of Geography, University of Western Ontario, 1151 Richmond Street, London, ON, N6A 5C2, Canada

    Jacek Malczewski

  2. Department of Geography, Ryerson University, 350 Victoria Street, Toronto, ON, M5B 2K3, Canada

    Claus Rinner

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Malczewski, J., Rinner, C. (2015). Heuristic Methods. In: Multicriteria Decision Analysis in Geographic Information Science. Advances in Geographic Information Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74757-4_6

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