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Integration of Spatial Information into Multi-Objective Genetic Algorithm for Spatial Optimal Location Based on GIS

Jinliang Hou, Haiqi Wang, Yujie Liu


This paper demonstrates the method integrate spatial information into multi-objective genetic algorithm to solve spatial optimal location problem based on GIS. Firstly, we have a brief introduction of Modified Non-dominated Sorting Genetic Algorithm. Secondly, we elaborate on the way of how the spatial information is introduced into NSGA-II and combined with GIS technology. Finally, we will verify this method by a case of selecting the optimal location of disease surveillance and control sites in Shandong Province, China. It is concluded that our method can converge at the Pareto-optimal set and is a feasible way of solving multi-objective spatial optimal location problem.


NSGA-II; GIS; Spatial Information; Spatial Optimal Location; Multi-objective.

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