Abstract
Solving linear variation al inequality by traditional numerical iterative algorithm not only can not satisfy parallel , but also its precision has much relationship with initial values. In this paper, a novel hybrid c oevolution ary particle swarm optimization is used to solve linear variational inequality, which sufficiently exert s the advantage of particle swarm optimization such as group search , global convergence and it satisfies the question of solving linear variational inequality in engineering . It also overcomes the influence of initial value s . Several numerical simulation results show that the c oevolution ary algorithm offers an effective way to solve linear variational inequality, high convergence rate, high accuracy and robustness .
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