NASH-PARTICLE SWARM OPTIMIZATION APPLIED TO THE ANALYSIS OF TIMBER MARKETS IN THE AMAZON FOREST

摘要

In the present work, we assess the application of the Nash-Particle Swarm Optimization (Nash-PSO) algorithm to the analysis of timber markets in the Amazon forest within a game theoretical framework. The usage of the PSO algorithm and the game theory's best response concept are the bases of the Nash-PSO algorithm, implemented for such analysis. With the Nash-PSO algorithm it is possible to analyze the interactions of players in a continuous space of strategies, for non-linear objective functions with a fast and accurate convergence. The results also demonstrate the viability of the Nash-PSO algorithm in the estimation of real values for government investment in forest areas.