Application of Ant Colony Optimisation Algorithm on Solid Waste Collection: A Case of University of Port Harcourt

Abstract

Ants are social insects and their behaviour is geared towards the survival of the colony rather than the survival of the individual. Because ants are almost blind, they move along by building chemical trails using a chemical substance called pheromone. These trails are used by ants to find the way to food or back to the colony, using the shortest or otherwise optimised path. This informed the development of The Ant Colony Optimization (ACO) Algorithm. This algorithm was applied to the waste collection system of the University of Port Harcourt so as to optimize the route for solid waste collection within the Institution. University of Port Harcourt has three campuses, namely Choba, Delta and University Park campuses which are networked within a radius of about 1.5 km, separated by two expressed ways. University Park was split into two, Section 1 and Section 2 for this study. The primary data used for this study was gotten with the help of the Global Information System, personal observation and monitoring of waste collection points and tours within the Institution. At the end of the optimization process, the ACO was able to reduce the tour path for Choba Park by 937.66 m, Delta Park by 1255.99 m, Abuja Park section 1 by 3779.89 m and Abuja Park Section 2 by 1875.15 m representing 33.5%, 31.43%, 51.48% and 32.16%, respectively. However, considering the physical nature of the built environment, a Best Tour Path (BTP) rather than the optimized path was chosen. This gave a total distance reduction of about 16% cumulatively.