Waste collection of medical items under uncertainty using internet of things and city open data repositories: a simheuristic approach

Abstract

© 2022. IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksIn a pandemic situation, a large quantity of medical items are being consumed by citizens globally. If not properly processed, these items can be pollutant or even dangerous. Inspired by a real case study in the city of Barcelona, and assuming that data from container sensors are available in the city open repository, this work addresses a medical waste collection problem both with and without uncertainty. The waste collection process is modeled as a rich open vehicle routing problem, where the constraints are not in the loading dimension but in the maximum time each vehicle can circulate without having to perform a mandatory stop, with the goal of minimizing the time required to complete the collection process. To provide high-quality solutions to this complex problem, a biased-randomized heuristic is proposed. This heuristic is combined with simulation to provide effective collection plans in scenarios where travel and pickup times are uncertainPeer ReviewedPostprint (author's final draft