Sparse search algorithm for a waste collection problem in an Argentine case study

Abstract

The growth of urbanization and rising consumption rates are putting pressure on urban systems to efficiently manage municipal solid waste (MSW). Waste collection, in particular, represents one of the most complex challenges in MSW management. Therefore, it is essential to develop computational tools to support decision-makers. In this work, a scatter search algorithm is proposed to address the waste collection problem. Few studies apply this algorithm, which has proven efficient in other routing problems, to real-world waste management problems. Results obtained from real-world instances in an Argentine city (Bahía Blanca) show that the algorithm is competitive. For small instances, the results obtained are equivalent to those of an improved exact method with valid inequalities, although with a longer computational time (as expected). However, for larger instances, the algorithm significantly improves the results of this exact method and requires considerably less computational time. Thus, sparse search proves to be a competitive algorithm for solving garbage collection problems.