Municipal waste collection is a critical process due to its high operational costs. This study aimed to identify the key operational factors affecting total collection costs in horizontally structured cities and to determine optimal ranges for three key operational variables. The study was conducted in three stages: spatial data collection using GIS, field surveys, and model building via Excel-based calculations across 45 scenarios. The three variables identified as most influential were collection frequency, compactor truck capacity, and crew size. The results indicate that collection frequency is the dominant factor in reducing costs, followed by compactor truck capacity and then workforce allocation. Collection frequency was limited to once every three days to prevent the degradation of organic waste. A 4-ton compactor truck was found to be the most suitable option for the street widths in the study area, while an optimal crew size of three workers per truck (excluding the driver) provided the best balance between labor efficiency and operational cost. The regression model achieved a high explanatory power (R² = 0.888), demonstrating that nearly 89% of the cost variability is explained by these parameters.