The dimensions of Mathematical and Computational Modeling prescribed to Environmental Management

• Autor(a) principal: Costa, Denis Carlos Lima
• Data de Publicação: 2020
• Outros Autores: Costa, Heictor Alves de Oliveira, Castro, Ana Paula Simões, Cruz, Edson Costa, Azancort Neto, Julio Leite, Cruz, Brennus Caio Carvalho da
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Research, Society and Development
• Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/9013
• topic: Desenvolvimento sustentável; Método dos pontos interiores; Otimização da matriz de critérios; Método de Cramer; Aterro sanitário.; Sustainable development; Interior points method; Optimization of the criteria matrix; Cramer's method; Landfill.; Desarrollo sostenible; Método de puntos interiores; Optimización de la matriz de criterios; Método de Cramer; Relleno sanitario.

The numerous scientific works, recently released, on projects applied to sustainable development, have considered a combination of methods such as AHP (Analytical Hierarchy Process) and GIS (Geographic Information Systems), for example. These procedures enable the identification of the main criteria, useful in the cadastral formulation, in a numerical format, for the problem of solid waste. This article presents a Mathematical and Computational Modeling Process (PM2C), which benefits from the response managed by the AHP and GIS methods, implementing functional relationships that adjust the n dimensions of the Criteria Matrix. The main objective of this work is to establish the Conventional and Optimal Solutions for the problem of the area location conducive to the construction of a landfill. The strategies, mathematical and computational, employ the Cramer Method and the Interior Points Method (Prime-dual) in the making of the algorithms. The results, expressed in analytical and graphical forms, show the individual values for each criterion involved in the phenomenon. The comparison, between the solution matrices, denotes the importance of incorporating the initial conditions, related to social and economic effects, and environmental security restrictions, in the modeled algorithms. Based on these premises, it was possible to simulate scenarios that demonstrate, with the highest precision, the best values of the criteria useful for decision making in the selection of the optimal area for the implementation of a landfill.