<p>Existing technology can handle heavy metals in hazardous wastes (HW) to a certain extent, but there are still potential pollution hazards. Therefore, optimizing HW transfer and treatment, especially by considering heavy metal pollution resulting from different treatment technologies, is of paramount importance. This study constructs a transfer and treatment network based on treatment technologies and establishes a multi-objective optimization model that incorporates heavy metal pollution. Using data on HW with high heavy metal content, the network is optimized concerning cost, risk and heavy metal pollution. Compared with the three single-objective scenarios, the multi-objective solution achieved a better balanced trade-off among cost, risk and heavy metal pollution, with a cost of 12,250 *10³ USD, a risk of 495 persons*ton and a heavy metal pollution index of 1285. Furthermore, the sensitivity analyses confirm the model robustness, while simultaneously highlighting that greater emphasis on heavy metal pollution and higher recovery rates (&gt; 0.9) are critical factors for improving optimization performance. Additionally, correlation analysis reveals a positive relationship between heavy metal pollution and cost. This study provides a novel optimization framework for HW transfer and treatment, with its results also offering valuable insights for heavy metal pollution control and the formulation of management policies.</p>