Recently, a multi-source, raw material allocation form of Weber’s classic single-facility location problem was rediscovered and recognized for its significance in contemporary planning and decision-making. This variation of the Weber problem investigates the optimal location of a production plant while permitting the selection of each required raw material source. This paper reviews Weber problem, mainly focusing on its extension incorporating multiple facilities. A multi-plant Weber problem involving resource allocation is formulated to highlight the allocation selection among many sources of given raw material inputs, which has not yet been implemented in existing continuous multi-plant location problems. An efficient solution approach is developed to address the computational intensity of the proposed model and is developed entirely based on open-source Python packages. Application findings demonstrate that the utility and computational efficiency of the developed solution algorithm to address this nonlinear problem is much superior to those of the most advanced commercial optimization software.