首页> 外文期刊>RAIRO Operation Research >ON THE PROBLEM OF MINIMIZING THE COST WITH OPTICAL DEVICES IN WAVELENGTH DIVISION MULTIPLEXING OPTICAL NETWORKS: COMPLEXITY ANALYSIS, MATHEMATICAL FORMULATION AND IMPROVED HEURISTICS
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ON THE PROBLEM OF MINIMIZING THE COST WITH OPTICAL DEVICES IN WAVELENGTH DIVISION MULTIPLEXING OPTICAL NETWORKS: COMPLEXITY ANALYSIS, MATHEMATICAL FORMULATION AND IMPROVED HEURISTICS

机译:波长除法多元光学网络中用光学器件最小化成本的问题:复杂性分析,数学公式和改进的启发式

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The Fiber Installation Problem (FIP) in Wavelength Division Multiplexing (WDM) optical networks consists in routing a set of lightpaths (all-optical connections) such that the cost of the optical devices necessary to operate the network is minimized. Each of these devices is worth hundreds of thousands of dollars. In consequence, any improvement in the lightpath routing may save millions of dollars for the network operator. All the works in the literature for solving this problem are based on greedy heuristics and genetic algorithms. No information is known on how good are the solutions provided by these heuristics compared to the optimal solution. Besides, no proof that the problem is NP-Hard can be found. In this paper, we prove that FIP is NP-Hard and also present an Integer Linear Programming (ILP) formulation for the problem. In addition, we propose an implementation of the Iterated Local Search (ILS) metaheuristic to solve large instances of the problem. Computational experiments carried out on 21 realistic instances showed that the CPLEX solver running with our ILP formulation was able to solve 11 out of the 21 instances to optimality in less than two minutes. These results also showed that the ILS heuristic has an average optimality gap of 1% on the instances for which the optimal solution is known. For the other instances, the results showed that the proposed heuristic outperforms the best heuristic in the literature by 7%.
机译:波分复用(WDM)光网络中的光纤安装问题(FIP)在于路由一组光路(全光连接),从而使操作网络所需的光学设备的成本降至最低。这些设备中的每一个都价值数十万美元。结果,光路径路由的任何改进都可以为网络运营商节省数百万美元。文献中解决这个问题的所有著作都是基于贪婪启发式算法和遗传算法。与最佳解决方案相比,还没有信息可知这些启发式方法提供的解决方案有多好。此外,找不到问题出在NP-Hard的证据。在本文中,我们证明FIP是NP-Hard,并且还提出了解决该问题的整数线性规划(ILP)公式。此外,我们提出了迭代局部搜索(ILS)元启发式方法的实现,以解决问题的大型实例。在21个实际实例上进行的计算实验表明,使用我们的ILP公式运行的CPLEX求解器能够在不到两分钟的时间内将21个实例中的11个求解到最优。这些结果还表明,在已知最优解的情况下,ILS启发式算法的平均最优间隙为1%。在其他情况下,结果表明,所提出的启发式方法比文献中最好的启发式方法高出7%。

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