Solving the frequency assignment problem by using meta-heuristic methods

Baris Satar, A. Akbulut, Guven Yenihayat, Tolga Numaoglu, A. Yargicoglu, A. Yılmaz
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Abstract

Frequency assignment, as a subclass of general assignment problem, is a non-deterministic polynomial-time hard (NP-hard) optimization problem. Main difficulty in these types of problems is the time required to find an optimum solution, since the solution time increases exponentially as the size of the problem grows. To solve the problem in a limited computation time, meta-heuristic methods are adopted. In this study, a frequency assignment problem with conflicting objectives is described. This multi-objective optimization problem is reduced to a single objective one using a scalarization approach. Genetic Algorithm and Particle Swarm Optimization are used to find a solution to the problem. Comparisons of the performances of alternative methods are carried out for the identified problem. Results show that the proposed methods can get a solution which is quite acceptable in terms of interference levels.
用元启发式方法求解频率分配问题
频率分配是一般分配问题的一个子类,是一个非确定性多项式时间难优化问题。这类问题的主要困难是找到最优解所需的时间,因为解的时间随着问题规模的增长呈指数增长。为了在有限的计算时间内解决问题,采用了元启发式方法。本文描述了一个具有冲突目标的频率分配问题。利用标量化方法将多目标优化问题简化为单目标优化问题。采用遗传算法和粒子群算法对该问题进行求解。针对所确定的问题,对各种方法的性能进行了比较。结果表明,所提出的方法可以得到在干扰水平方面相当可接受的解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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