中文摘要：

近年来，房地产价格持续快速上涨，居民住房问题日益突出，为了缓解中低收入居民住房问题，政府兴建了大批保障性社区．而当前保障性社区公共服务设施普遍存在配置不完善，供给滞后，低效与供给过剩同时存在的问题，导致人口入住过程缓慢，入住率低．这不仅影响到居民的生活质量，同时也影响到保障效果的实现及和谐社会的构建．文章以上海市保障性社区为研究对象，在多目标约束条件下，构建了可以清晰表达保障性社区公共服务设施配置空间的多目标微粒群算法（particle swarm optimization，PSO）优化模型，并基于所构建模型，实证分析保障性社区公共服务设施配置优化模拟，在此基础上求出了公共服务设施最优配置方案，这对于提高保障性社区公共服务设施配置的科学性和合理性，完善社区公共服务设施的配置理论，具有较大的理论意义和实践意义．

英文摘要：

In recent years, as the real estate prices continue to rise rapidly, the problem of the residents＇ housing increasingly prominent. In order to alleviate the housing problems of low-income residents, the government built a large number of indemnificatory communities. However, the configuration problem of public service facility is widespread imperfect, and the supply is lag and inefficient or excess, which leads to the process of population check-in is slowly and low occupancy rate. The situation affects the quality of residents＇ life, also the realization of indemnification and the harmonious society building. Taken a Shanghai indemnification community as an example, the paper built the particle swarm optimization （PSO） models that can clearly express the space of supply for indemnificatory community public service facility under the condition of multi-objective constraint. Besides, in order to improve community public service facility configuration to be scientific and rational, also to perfect the configuration theory of community public service facilities and achieve the best use of public service facility, the paper empirical analyzed affordable community public service facilities configuration optimization simulation and application of research strategy, which has a certain theoretical and practical significance.