Open Access Open Access  Restricted Access Subscription or Fee Access

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

Jinliang Hou, Haiqi Wang, Yujie Liu

Abstract


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.

Keywords


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

Full Text:

PDF

Refbacks

  • There are currently no refbacks.


Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.