Smart waste management by using integer programming

In this work, we have addressed the location of bins in two real cities (Montevideo and Buenos Aires) as an optimization problem. The idea is to provide an efficient waste management system that provides the best quality-of-service possible, while minimizing the budget.

We have defined the problem and we have addressed it by using exact optimization methods integer programming and a greedy algorithm based on PageRank.

The full paper can be found here

A bi-objective integer programming model for locating garbage accumulation points a case study

Abstract

Enhancing efficiency in Municipal Solid Waste (MSW) management is crucial for local governments, which are generally in charge of collection, since this activity explains a large proportion of their budgetary expenses. The incorporation of decision support tools can contribute to improve the MSW system, specially by reducing the required investment of funds. This article proposes a mathematical formulation, based on integer programming, to determine the location of garbage accumulation points while minimizing the expenses of the system, i.e., the installment cost of bins and the required number of visits the collection vehicle which is related with the routing cost of the collection. The model was tested in some scenarios of an important Argentinian city that stills has a door-to-door system, including instances with unsorted waste, which is the current situation of the city, and also instances with source classified waste. Although the scenarios with classified waste evidenced to be more challenging for the proposed resolution approach, a set of solutions was provided in all scenarios. These solutions can be used as a starting point for migrating from the current door-to-door system to a community bins system.