Waste collection vehicle routing problem on HPC infrastructure

Abstract

Waste companies need to reduce the cost of collection of the municipal waste, to increase the separation rate of different types of waste, or site of waste source. The collection of waste is an important logistic activity within any city. In this paper, we mainly focus on the daily commercial waste collection problem. One of the approaches for how to resolve this problem is to use optimization algorithms. Ant colony optimisation metaheuristic algorithm (ACO) was used to solve the problem in this paper. This algorithm was adapted for a real data set (Waste Collection). The aim of this paper is to adapt the ACO algorithm and run it on HPC infrastructure to resolve the waste collection problem. We used High-End Application Execution Middleware (HEAppE), that provides smart access to the supercomputing infrastructure (in our case Salomon cluster operated by IT4Innovations National Supercomputing Centre in the Czech Republic). The results showed that the paralelisation of the algorithm is beneficial and brings together with the supercomputing power the possibility to solve larger problems of this type.