A decision support system for waste collection modeled as TOPTW variant

Abstract

Usually the selective collection of municipal solid waste is expensive and has low efficiency, especially when it is done on a large scale. Despite the abundance of commercially available software for fleet management, managers receive scant help from it because it typically is not able to deal with sequencing problems or revising plans and schedules dynamically during process execution. We consider waste collection as a process that includes logistics topics such as transport and traffic problems, forecasting and operations scheduling, and fitted for improving or maximizing several performance measures. This is a novel approach, which we have been pursuing for the past few years and have proven to be amenable to mathematical modeling. This allows the use of optimization techniques, which promote recycling, the recovery of waste necessary to increase the resource efficiency of the economy, reducing the negative environmental impact of the use of natural resources. This paper discusses the model and a genetic algorithm to solve a new variant of the Team Orienteering Problem with Time Windows that can be used to deal with the selective collection of municipal solid waste, allowing for a reduction in logistic costs.