Abstract
The exponential growth of electronic waste (e-waste) in urban areas poses significant environmental, logistical, and economic challenges. Efficient management of reverse logistics networks is essential for sustainable e-waste handling, especially in rapidly developing cities like Indore, Madhya Pradesh. This study presents an optimization framework based on Operations Research (OR) techniques to enhance the collection, routing, and processing of e-waste. A Mixed Integer Linear Programming (MILP) model is developed with the objective of minimizing total costs, including collection, transportation, and handling, while adhering to real-world constraints such as vehicle capacities, time windows, and facility limits. Primary and secondary data were gathered from local municipalities, recyclers, logistics providers, and informal aggregators. The model is solved using MATLAB/CPLEX, with GIS-based mapping for spatial optimization and Arena simulation for evaluating dynamic flows. The results r