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Primary healthcare plays a pivotal role in enhancing health conditions. In Singapore, such services are predominantly manifested through the implementation of the Community Health Assistance Scheme (CHAS). CHAS is an initiative aimed at providing fundamental preventive and therapeutic services, especially for those seniors and low‐income adults with chronic diseases. In spite of considerable efforts in policy and research in this domain, there is a dearth of studies focusing on the spatial optimization of these primary healthcare services. In this study, an innovative multi‐objective medical service facility siting model has been developed based on coarse‐grained parallel genetic algorithm to address the intricate challenges associated with the optimization of locations for CHAS clinics. The proposed optimization model aims to simultaneously maximize accessibility, minimize inequity, and minimize the number of clinics. The successful application of this model in the siting of CHAS clinics in Singapore demonstrates its effectiveness in enhancing residents' access to healthcare services. Apart from its novel academic contributions to the field of spatial optimization of primary healthcare facilities in general, we have also discussed the inherent limitations and identified certain aspects as the future directions of this research. [ABSTRACT FROM AUTHOR]