The objective of this study is to identify the optimal location for weather radar networks in order to enhance air traffic control (ATM) in adverse conditions. This paper presents MS-ROASMA, a hybrid algorithm combining modified remora optimisation and slime mould algorithms. MS-ROASMA is utilised for the generation of optimal location radar networks (OLRNs) based on digital elevation models. The algorithm employs a discrete approach to spatial solutions, utilising nested optimisation for population diversity and incorporating self-adaptive positioning updates. MS-ROASMA is capable of minimising partial beam blockage (PBB) while simultaneously considering elevation and distance constraints. The findings demonstrate that the modified algorithms outperform the original ones for small populations, thereby providing an effective solution for optimal radar placement under computational constraints.