Abstract
The paper presents a decision support approach to solving problems characterized by spatially-explicit decision variables, multiple objectives, and preferences for ancillary decision criteria. The approach offers a three-step workflow, in which Pareto non-dominated solutions to a multi-objective decision problem are generated with a spatially adaptive genetic algorithm, objective value trade-offs are examined in an interactive graphics environment, and the selected solution alternatives are evaluated on the bases of ancillary multiple criteria. The three-step workflow is demonstrated on the example of a selection problem involving alternative configurations of sensors for radioactivity monitoring in a trans-border region including the state of Lower Saxony in Germany and the Netherlands. The presented approach promotes the search for diverse, non-dominated solution alternatives by coupling a fuzzy logic system with spatially adaptive genetic operators. The three-step workflow offers a comprehensive approach to spatial decision support starting with diverse option generation, through exploration of decision objective trade-offs, to multiple criteria evaluation of the selected non-dominated decision alternatives.
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