Ravi Sankar Barpanda, A. K. Turuk, B. Sahoo, B. Majhi
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引用次数: 16
摘要
波分复用(WDM)光网络中的路由和波长分配(RWA)问题假定为连接请求分配用于创建光路的路由和波长。RWA问题属于组合优化问题的一类。发现RWA问题的最优解是np困难的,因此适合启发式方法。我们构造了一个整数线性规划(ILP)问题,将RWA问题建模为一个优化问题,并利用遗传算法(GA)启发式求解所构造的ILP,在多项式时间内得到一个近似最优解。我们的主要优化目标是建立个体之间拥塞最小的连接请求。次要目标是最小化跳数、路由长度、用于满足所有光路请求的光纤链路数量。在ARPANET (Advanced Research Project Agency NETwork)网络上对基于遗传算法的启发式算法进行了仿真,并将多目标遗传算法与单目标遗传算法的结果进行了比较。结果表明,在优化不同网络参数时,多目标遗传算法优于单目标遗传算法。
Genetic Algorithm techniques to solve Routing and Wavelength Assignment problem in Wavelength Division Multiplexing all-optical networks
Routing and Wavelength Assignment (RWA) problem in Wavelength Division Multiplexed (WDM) optical networks assumes assigning the routes and wavelengths to be used to create the lightpaths on behalf of the connection requests. The RWA problem belongs to the class of combinatorial optimization problems. The optimal solution to the RWA problem is found to be NP-hard and thus suited to heuristic approaches. We formulate an Integer Linear Programming (ILP) problem to model the RWA problem as an optimization problem and solve the formulated ILP using Genetic Algorithm (GA) heuristic to obtain a near optimal solution in polynomial time. Our primary optimization objective is the establishment of connection requests with minimum congestion among the individuals. The secondary targets are to minimize the hop count, route length, the number of fiber links utilized to honor all the lightpath requests. The GA based heuristic approach is simulated on ARPANET (Advanced Research Project Agency NETwork) and the results obtained for the multi objective GA are compared with the single objective GA. The results show that multi objective GA performs better than single objective GA while optimizing different network parameters.