基于免疫粒子群算法的广义Nash均衡问题求解

针对广义Nash均衡求解问题, 提出了一种免疫粒子群算法。首先利用非线性互补问题, 将广义Nash均衡问题转换为非线性方程组问题, 然后把免疫算法中抗体的免疫记忆功能和抗体浓度抑制机制引入基本粒子群算法, 设计了一种免疫粒子群算法。最后通过数值实验表明, 该算法保持了粒子群种群多样性, 增强了粒子群算法的全局寻优能力, 加快了算法的收敛速度, 具有较好的性能。

Solving generalized Nash equilibrium problem based onimmune particle swarm algorithm

This paper presented an immune particle swarm algorithm for solving generalized Nash equilibrium problem. First it reformulated the generalized Nash equilibrium problem as the nonlinear equations problem by the nonlinear complementarity problem. Then it designed an immune particle swarm algorithm by involving the immune memory function and the antibody concentration inhibition mechanism into the original swarm algorithm. Finally the computer simulation results demonstrate that the proposed algorithm is effective and it not only keeps the variety of the original swarm, but also improves the abilities of seeking the global optimization result and the evolution speed of convergence.