This research studies the potential of bikeshare services to bridge the gap between Affordable Housing Communities (AHC) and transit services to improve transport accessibility for the residents. In doing so, the study develops an agent-based simulation optimization modeling (ABM) framework for the optimal design of the bikesharing station network considering improving accessibility as the objective. The study discusses measures of accessibility and uses travel times in a multi-modal network. Focusing on the city of Sacramento, CA, the study gathered information related to affordable housing communities, detailed transit services, demographic information, and other relevant data.  This ABM framework is used to run three stages of travel demand modeling: trip generation, trip distribution, and mode split to find the travel time differences under the availability of new bikesharing stations. The model is solved with a genetic algorithm approach. The results of the optimization and ABM- based simulation indicate the share of bike and bike & transit trips in the network under different scenarios. Key results indicate that about 60% of the AHCs are within 25-minute active travel time when the number of stations ranges from 25 to 75, and when the number of stations is increased to 100, most AHCs are within 40 mins of active mode distance and all of them are less than an hour away. In terms of accessibility, for example, having a larger network of stations (e.g., 100) increases by 70% the number of Points of Interest (for work, health, recreation, and other) within a 30-minute travel time. This report then provides some general recommendations for the planning of the bikesharing network considering information about destination choices as well as highlighting the past and current challenges in housing and transit planning.