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A Memetic Immunological Algorithm for Resource Allocation Problem

机译:资源分配问题的模因免疫算法

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In this research work, we present a combination of a memetic algorithm and an immunological algorithm that we call Memetic Immunological Algorithm - MIA. This algorithm has been designed to tackle the resource allocation problem on a communication network. The aim of the problem is to supply all resource requested on a communication network with minimal costs and using a fixed number of providers, everyone with a limited resource quantity to be supplied. The scheduling of several resource allocations is a classical combinatorial problem that finds many applications in real-world problems. MIA incorporates two deterministic approaches: (1) a local search operator, which is based on the exploration of the neighbourhood; and (2) a deterministic approach for the assignment scheme based on the Depth First Search (DFS) algorithm. The results show that the usage of a local search procedure and mainly the DFS algorithm is an effective and efficient approach to better exploring the complex search space of the problem. To evaluate the performances of MIA we have used 28 different instances. The obtained results suggest that MIA is an effective optimization algorithm in terms of the quality of the solution produced and of the computational effort.
机译:在这项研究工作中,我们提出了模因算法和免疫学算法(称为模因免疫学算法-MIA)的组合。设计该算法以解决通信网络上的资源分配问题。该问题的目的在于以最小的成本并且使用固定数量的提供者来提供通信网络上所请求的所有资源,每个提供者具有有限的资源数量。几种资源分配的调度是一个经典的组合问题,可在实际问题中找到许多应用。 MIA包含两种确定性方法:(1)基于对邻域的探索的本地搜索运营商; (2)基于深度优先搜索(DFS)算法的分配方案的确定性方法。结果表明,使用局部搜索程序(主要是DFS算法)是一种更好地探索问题的复杂搜索空间的有效途径。为了评估MIA的性能,我们使用了28个不同的实例。获得的结果表明,就生成的解决方案的质量和计算量而言,MIA是一种有效的优化算法。

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