Greedy Heuristics for the Maximum Covering Location Problem: A case study of Optimal Trashcan Location in Kampung Cipare-Tenjo-West Java

Abstract

Having a rapidly growing economy without proper waste handling system and infrastructure has made Indonesia one of the top contributors of plastic marine debris in the world: 3.22 million metric tons of mismanaged plastic waste per year. The mismanagement of waste is worse in the rural area where the number of available public trashcan is limited and the people have no idea where their trash actually ends up. In this research, a case study of waste management in Kampung Cipare-Tenjo, a small village 80 kilometers away from Jakarta, is conducted. The biggest purpose of the research is to educate people about sanitation and waste management, initiated by computing the most optimum number and locations of the public trashcans. The problem is addressed as Maximum Covering Location Problem (MCLP) to determine a set of facility locations that maximizes the total demand population served by the facilities within a prespecified maximum service distance. Two greedy heuristics algorithms: Greedy Adding Algorithm (GAA) and Greedy Adding with Substitution Algorithm (GAAS) are utilized to solve the problem. A sensitivity analysis is also done to check the result on the effect of trashcan number and maximum service distance to demand coverage. Out of the 26 location candidates, it is concluded that the final 10 locations are the most optimum in terms of demand coverage and service distance. The result of the research has been implemented in Kampung Cipare-Tenjo.