Spatial planning via extremal optimization enhanced by cell-based local search

2nd International Conference on Mathematical Modeling in Physical Sciences 2013

物理学;数学

Sidiropoulos, Epaminondas^1

Faculty of Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece^1

关键词: Combinatorial optimization problems;    Extremal optimization;    Hybrid method;    Land Use Planning;    Objective function values;    Self-organized critical models;    Spatial optimization;    Spatial planning;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/490/1/012071/pdf
DOI  :  10.1088/1742-6596/490/1/012071

来源: IOP

【 摘 要 】

A new treatment is presented for land use planning problems by means of extremal optimization in conjunction to cell-based neighborhood local search. Extremal optimization, inspired by self-organized critical models of evolution has been applied mainly to the solution of classical combinatorial optimization problems. Cell-based local search has been employed by the author elsewhere in problems of spatial resource allocation in combination with genetic algorithms and simulated annealing. In this paper it complements extremal optimization in order to enhance its capacity for a spatial optimization problem. The hybrid method thus formed is compared to methods of the literature on a specific characteristic problem. It yields better results both in terms of objective function values and in terms of compactness. The latter is an important quantity for spatial planning. The present treatment yields significant compactness values as emergent results.