In recent years, global coffee consumption has soared, surpassing 10.7 million tons in 2022/23. This trend has led to an increase in spent coffee grounds (SCG), with each kilogram of soluble coffee yielding nearly 2 kg of wet waste. Much of this waste ends up in landfills, where it emits methane, a greenhouse gas that is 25 times more potent than carbon dioxide. This environmental challenge requires the development of an effective waste management system specifically designed for SCG. This paper investigates a method to optimize coffee waste collection in urban areas, using a combined approach that integrates a vehicle routing problem (CVRP) with a discrete event simulation model (DES). The CVRP model is used to find the best collection routes minimizing the travel distance while respecting vehicle capacity and operating restrictions. The model is informed by data such as the locations of coffee shops and treatment centers, waste generation estimates based on consumption trends, and relevant demographic information. The DES component simulates the collection process in various scenarios, offering performance insights when waste levels or operating conditions fluctuate. By combining these methods, this study provides a framework that serves as a scalable solution that can be adapted to other urban settings, contributing to the broader goal of sustainable urban waste management.