Analysis of garbage collection network of Colombo district using centrality measures

Waste management is a common problem faced by all developing countries. Colombo city faces the biggest garbage problem than other cities in Sri Lanka. Even through many studies were carried out for waste management problem using different approaches, there were very few research findings were available using graph theoretical approach. In this research, applications of graph theory in garbage collection procedure are depicted. The study mainly focuses on analyzing the garbage collection procedure of Colombo municipal council area in western province through constructing garbage collection network and using centrality measures. Centrality measures are used to compute the importance of any node in a network. Colombo municipal area divides into 6 main administrative districts, and each of these is divided into municipal wards with several junctions and streets. Garbage collection network was initially constructed by assigning a node by a location in google map, and an edge by a street or a path between two locations. Constructed network is an undirected unweighted graph and betweenness, closeness, degree, and eigenvector centrality measures are used to find central locations of the network. By identifying central locations, some machines or recycling trucks can be placed in that central places to deposit the waste. Next, a weighted graph was constructed by taking the weights of an edge as a fraction of weight of collected garbage between two locations. Collected garbage weights and betweenness and degree centrality values for weighted graph are used to identify the shortest paths between central nodes in each municipal ward. Garbage collection trucks can be followed this shortest path in order to reduce their fuel cost and collection time.