Half a billion simulations: evolutionary algorithms and distributed computing for calibrating the SimpopLocal geographical model

Authored by Denise Pumain, Clara Schmitt, Sebastien Rey-Coyrehourcq, Romain Reuillon

Date Published: 2015

DOI: 10.1068/b130064p

Sponsors: European Research Council (ERC)

Platforms: No platforms listed

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

Multiagent geographical models integrate very large numbers of spatial interactions. In order to validate these models a large amount of computing is necessary for their simulation and calibration. Here a new data-processing chain, including an automated calibration procedure, is tested on a computational grid using evolutionary algorithms. This is applied for the first time to a geographical model designed to simulate the evolution of an early urban settlement system. The method enables us to reduce the computing time and provides robust results. Using this method, we identify several parameter settings that minimize three objective functions that quantify how closely the model results match a reference pattern. As the values of each parameter in different settings are very close, this estimation considerably reduces the initial possible domain of variation of the parameters. Thus the model is a useful tool for further multiple applications in empirical historical situations.

Tags

Genetic Algorithms Agent-based models Dynamics Archaeology Optimization spatial interaction System States