The primary objective of this research is to develop an order load-based model for assembly line balancing in manufacturing industries. Accordingly, this study endeavors to examine the role of order weights and their impact on the balancing and coordination of workstations through the design and validation of a multi-objective model. The theoretical objective of this research is to develop an appropriate framework for assembly line balancing considering order load, while its practical objective is to identify factors influencing waste in the production process and to propose a model for controlling and improving the performance of assembly lines with emphasis on order weights. In terms of nature, this research is fundamental-applied; regarding the implementation method, it is descriptive; and in terms of temporal dimension, it is cross-sectional. Data were collected through comprehensive literature reviews, direct observation of production lines, mapping of actual facility layouts, and semi-structured interviews and questionnaires administered to ten experts from four active manufacturing plants. For data analysis and model optimization, the Gurobi solver was employed for exact optimization, alongside an adaptive heuristic algorithm and MATLAB software to address the problem under dynamic order conditions. The results indicated that the developed multi-objective model, integrated with the hybrid heuristic algorithm, is capable of achieving more balanced workstation loads, reducing idle times, and significantly enhancing the productivity index of the assembly line. Furthermore, the concurrent utilization of the Gurobi solver to attain optimal solutions and the heuristic algorithm to accelerate convergence under order fluctuation conditions yielded the most effective performance.