ESTIMACIÓN DEL COSTO DEL SECUESTRO CARBONO, USANDO OPTIMIZACIÓN MULTIOBJETIVO Y LA TÉCNICA DE COLONIA DE HORMIGAS

Abstract

Because actions that contribute to mitigate climate change are important, this paper presents a tool to estimate the cost of
carbon sequestration in soils. The situation is modeled as a bi-objective optimization problem (minimizing the cost of carbon sequestration and maximizing the carbon absorption). The Ant Colony heuristic technique is applied to solve the problem, using the methodology proposed by Iredi (2001) to calculate the probability that an ant moves from node i to node j. The data of the estimation of carbon sequestration in the coffee plant, in six municipalities of the Sierra Norte of Puebla, was provided by the Department of Agricultural Research (DICA- ICUAP). We also used the information published by the National Institute of Statistics, Geography and Informatics (INEGI) about the costs of irrigation and labor coffee in those municipalities. Because the data of the six
municipalities, povided by DICA was not enough to generate the Pareto frontier, we developed a generator of artificial instances, in order to test the proposed algorithm. The evidence suggested that the parameters α and β are particularly important to calculate the probability that an ant moves from node i to node j, and the Pareto frontier, can be obtained with a number of iterations equal to 50% of the number of ants and a number of municipalities equal to ten. As results, we present the estimated costs of carbon sequestration per ton