Efficient management of solid waste remains a big challenge in most urban areas, especially in the Colombo area. Different studies have been done by several researchers over the years to find ways of improving waste collection systems. Route optimization has become one of the key focus areas, which could help in improving efficiency, reducing operational costs, and decreasing environmental and climatic impacts. This review will help us to identify the local and global findings on route optimization techniques in solid waste management, focusing on different approaches used to handle the challenges faced.
A study conducted in the Ratmalana area aimed at optimizing the MSW collection and transportation process to address the high operational costs. In this regard, the application of linear programming techniques has helped minimize the total distance of transportation along with fuel consumption and emission. Based on the secondary data pertaining to September 2020, the study revealed that optimization would reduce the daily travel distance by 31.23 km and thus would be cost-effective (R & MDN, 2022).
A study focused on Gampaha, the second most densely populated district in Sri Lanka, modified the maximum flow amount technique to optimize municipal solid waste (MSW) collection via the shortest path model. With the use of GIS tools and Google Maps, the researchers determined the optimum route, which reduced the daily travel distance to 858 km, representing more than a 10% enhancement; furthermore, the vehicle requirement was reduced from 10 to 8, further reducing the distance by 14.2% and vehicle allocation by 20%. These optimizations have created room for considerable cost savings, especially in fuel consumption, establishing the foreplay of mathematical modelling in waste management (Hakmanage & D.D.M. Jayasundara, 2018).
Another case study on the optimization of MSW collection by routed tractors and assigning road segments in Kurunegala involved a developed methodology. By making use of the Capacitated Arc Routing Problem and Solver Studio through the use of Binary Integer Programming, the researchers successfully reduced trips made by 19% every week and reduced traveled distance by up to 36%. The studies have shown that data-driven optimizations significantly enhance urban waste management system efficiency and contribute toward a reduction in operation costs, consumption of fuel, and carbon footprint (R. D. S. S. Rambandara et al., 2022).
The study, in Kampala, Uganda, found that by applying GIS tools in route optimization during waste collection, the travel distances and the number of trips were minimized, increasing cost savings. It further optimized the vehicle fleet capacity for efficient operation with reduced emissions and fuel consumption. Using the GIS tools, a new landfill was derived as the existing site neared its capacity. Travel distances are reduced, hence reducing costs and leaving the environment cleaner. Such an approach can be a great insight into effective waste management in cities like Colombo in Sri Lanka (Kinobe et al., 2015). These studies highlight the importance of route optimization in improving waste management efficiency. By applying these insights, we can develop adaptable strategies to enhance Colombo’s waste collection system.