Mobility hubs are interconnected nodes where several travel modes, private or public, are integrated. They aim to ensure an efficient inter-modality and to prioritize sustainable transportation. Determining their best location is a new fertile research area attracting considerable attention. Although past studies have addressed the location conundrum using the hub location problem (HLP) models, much of the literature has overlooked the aspect of social equity. In this context, social equity refers to the distribution of advantages and disadvantages of a particular policy across diverse social strata, avoiding any social exclusion and discrimination. This study intends to select mobility hub locations that achieve balanced social justice and optimal coverage. It adopted the single allocation ??-median hub with a fixed cost model, where the fixed cost encapsulated equity and coverage indices. For equity, the Gini index was derived using social quantile group data. The meta-heuristic method Genetic Algorithm was exploited to solve the HLP optimization. This model displayed a good performance with a high fitness value of around 7.7e7, selecting nine (9) districts. Results of the first optimization step di underscored that locating mobility hubs within mixed land-use areas inhabited or frequented by low to medium-income strata helps promote equitable access and social justice while enhancing sustainable transportation ridership and coverage.