Remeo: Cutting costs and reducing emissions with route optimization

Alternative scenarios calculated using available data 

This project focused on optimizing waste container collection routes in a major Finnish city using an algorithm developed by twoday. The solution involved a tool that pulled data from Remeo's information system, reformatted it for optimization, and then returned the results in a format compatible with Remeo's system. 

The optimization process created daily driving routes for the entire week, factoring in shift-specific limitations. A new algorithm was also developed to evenly distribute container emptying tasks over multiple weeks. Various alternative scenarios were analyzed using available data, such as variations in the number of operational days available for collection. 

Key performance indicators for measuring Remeo’s operational efficiency included total route length, driving time, and workload balancing. Workload balancing ensures a consistent distribution of tasks across the week, to ensure daily shifts are evenly distributed. Overly long routes lead to overtime, while overly short routes waste valuable working hours. 

The container emptying intervals range from 1 to 60 days, which allows for a wide variety of planning options which significantly increases the complexity of the calculations. Besides container locations and emptying schedules, certain locations require consideration of specific constraints regarding emptying frequency.