关键词: 系统评价, 层次分析法, 粒子群算法, 自适应策略

Abstract: System evaluation is one of the focuses in system engineering theory and practice research.As one main method of system evaluation in correcting judgment matrix，CAHP has a high-dimensional，multi-constrained nonlinear optimization problem.On the basis of particle swarm optimization algorithm，the thesis designs the WS small-world network with non-zero degree of node as a neighbor particle structure，adaptively adjusts population density，improves population diversity and introduces the boundary correction strategy to prevent the particles into the local optimal solution，which composes PSO in the consistency of the judgment matrix of correcting AHP.This research not only expands the application area of PSO，but also provides a new way to solve nonlinear optimization problems in system evaluation.Through analyzing an example of the sustainable use system of water resource in the lake，the results are stable and highly precise.

Key words: systematic evaluation, analytic hierarchy process, particle swarm optimization, adaptive strategy