Particle swarm optimization for correcting judgment matrix consistency in analytic hierarchy process

Systematic evaluation is the hot and difficult of systems engineering theory and practice, of which, one of the main methods is to correct the CAHP of matrix, but some high-dimensional, multi-constrained nonlinear optimization problem will arise in the evaluation process. This research, based on particle swarm optimization algorithm, designs the WS small-world network with the node degree not equal 2 as a neighbor particle structure and adaptively adjusts the diversity of population density of population groups, as well introduces the boundary correction strategy. Through analyzing an example of the sustainable use of lake water resource system, the results are stable and with high precision.