METAHEURISTIC ANALYSIS IN REVERSE LOGISTICS OF WASTE

This paper focuses in the use of search metaheuristic techniques on a dynamic and deterministic model to analyze and solve cost optimization problems and location in reverse logistics, within the field of municipal waste management of Malaga (Spain). In this work we have selected two metaheuristic techniques having relevance in present research, to test the validity of the proposed approach: an important technique for its international presence as is the Genetic Algorithm (GA) and another interesting technique that works with swarm intelligence as is the Particles Swarm Optimization (PSO). These metaheuristic techniques will be used to solve cost optimization problems and location of MSW recovery facilities (transfer centers and treatment plants).