Support system for decision making and management of solid waste using computational intelligence

Abstract

Sustainable development, conservation and protection of the environment are issues that attract the attention from all sectors of the society, including government and business. This concern is well-known and the discussion on the subject at national level led to the elaboration of legislations and technical norms guided by the concept of sustainability, such as Brazilian Federal Law No. 12,305 of August 2, 2010, which created the National Solid Waste Policy (Política Nacional de Resíduos Sólidos - PNRS). This law strengthened the principles of integrated and sustainable waste management, including, among other novelties, shared responsibility, reverse logistics, solid waste management plans (BRASIL, 2010) and, more recently, Reverse Logistics. In addition to the legal aspects, the strong market demand for businesses aligned with sustainability, mainly those related to the management of its own solid waste, grows considerably.Therefore, in a market that asks for sustainable organizations, all members of the productive chain in different sectors must know and manage the legal requirements that guide waste practices, ensuring the packaging, storage, transport, destination, reverse logistics and environmentally adequate final disposal, taking into account the current legislation in a safe, effective and modern way, justifying this proposal.In this way, the present project has as prerogative the commercial development of the Actio LR System, technology developed in 03 modules: solid waste management, collection points and reverse logistics. To this purpose, it is expected computational mechanisms to be implemented such as Text Mining and Machine Learning in order to improve the decision-making processes in the Waste Management. The research method adopted will be: text mining for the solid waste management module, which is a strategy for extracting knowledge from a large set of information, and the set of information to be used includes federal and state laws, as well technical standards on solid waste. In addition, the Artificial Immune Systems method will be adopted for improvements and modernization of the process and the Reverse Logistics module. Artificial Immune Systems comprises a wide range of algorithms that are inspired by the animal's immune system. Because of its inspiration coming from communication networks (between cells of the immune system) already existing in nature, as a good solution to the task of reverse logistics. In addition, outliers detection techniques can be implemented aiming at real-time discovery of some fault or error in the logistics process, such as a collection truck that passes at a collection point outside the usual time window.As a result, it is expected to commercially improve and make the Actio LR system more technologically robust with innovative computational strategies, applied in the knowledge discovery with greater accuracy, helping to make solid waste management decisions more autonomously (or semi-autonomously), possible. The present system will benefit public and private administrations that need to manage their waste in an integrated and more efficient way, allowing a better fulfillment of their goals, providing information to define practices and processes related to generation, management routines, handling, destination and reverse logistics, always based on current law. (AU)