基于改进粒子群算法的光网络波长分配方法研究

Research on wavelength assignment in optical networks based on improved particle swarm optimization

为合理解决光网络波长分配问题,提出了基于改进粒子群算法的光网络波长分配方法。建立光网络模型分析光网络节点的波长变换信息后,以波长分配总代价最小为目标,构建波长分配目标函数;使用Rockafellar乘子法将光网络波长分配优化问题变换成不存在约束条件的优化问题,并建立光网络波长分配问题可能解的并行子群,利用改进粒子群算法求解波长分配目标函数,获取光网络波长分配问题全局最优解。实验结果验证:此方法在执行光网络波长分配任务时,可考虑到节点差异关系,变换波长分配策略,快速收敛获取波长分配最优方案,避免光网络出现拥塞情况;还能够以风险最低为目的,实现光网络波长合理分配。

In order to reasonably solve the problem of wavelength assignment in optical networks, an optical network wavelength assignment method based on improved particle swarm optimization algorithm is proposed. After establishing the optical network model and analyzing the wavelength conversion information of optical network nodes, the wavelength allocation objective function is constructed with the goal of minimizing the total cost of wavelength allocation;The Rockafellar multiplier method is used to transform the optical network wavelength assignment optimization problem into an optimization problem without constraints, and the parallel subgroup of possible solutions of the optical network wavelength assignment problem is established. The improved particle swarm optimization algorithm is used to solve the wavelength assignment objective function to obtain the global optimal solution of the optical network wavelength assignment problem. The experimental results show that this method can consider the node difference relationship, transform the wavelength allocation strategy, quickly converge and obtain the optimal scheme of wavelength allocation, so as to avoid congestion in optical network;It can also realize the reasonable wavelength allocation of optical network for the purpose of minimum risk.