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Two grouping-based metaheuristics for clique partitioning problem

APPLIED INTELLIGENCE 2017年第2期47卷 430-442页

作者： Sundar, Shyam Singh, Alok Natl Inst Technol Raipur Dept Comp Applicat Raipur 492010 Madhya Pradesh India Univ Hyderabad Sch Comp & Informat Sci Hyderabad 500046 Andhra Pradesh India

Given a connected, undirected graph G = (V,E), where V is the set of vertices and E is the set of edges, the clique partitioning problem (CPP) seeks on this graph a partition of set V into minimum number of subsets such that each subset is a clique. The CPP is an -Hard problem and finds numerous practical applications in diverse domains like digital design synthesis, clustering etc. Despite its computational complexity and its numerous applications, only problem-specific heuristics have been developed so far for this problem in the literature. In this paper, two metaheuristic techniques - a steady-state grouping genetic algorithm and an artificial bee colony algorithm - are proposed for the CPP. Both the proposed approaches are designed in such a way that the grouping structure of the CPP is exploited effectively while generating new solutions. Since artificial bee colony algorithm is comparatively a new metaheuristic technique, special attention has been given to the design of this algorithm for the CPP and we came out with a new neighboring solution generation method utilizing solution components from multiple solutions. The proposed approaches have been tested on publicly available 37 DIMACS graph instances. Computational results show the effectiveness of the proposed approaches.

关键词： Clique partitioning problem grouping problem steady-state grouping genetic algorithm Artificial bee colony algorithm

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A hybrid evolutionary approach to the registration area planning problem

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APPLIED INTELLIGENCE 2014年第4期41卷 1127-1149页

作者： Chaurasia, Sachchida Nand Singh, Alok Univ Hyderabad Sch Comp & Informat Sci Hyderabad 500046 Andhra Pradesh India

The last two decades have witnessed a phenomenal growth in the number of cellular wireless network users which in turn stressed the need to utilize the limited network bandwidth in an efficient manner. The network bandwidth is consumed not only by user traffic, but also by control traffic needed for ensuring the mobility of users. As we don't have any control over the volume of user traffic, all attempts to efficiently use bandwidth are based on frequency reuse and minimizing the control traffic. The registration area planning (RAP) problem seeks a partition of the cells of the network into contiguous areas called registration areas so that the bandwidth consumed by control signals is minimized. RAP problem in an NP-Hard problem. In this paper, we present a steady-state grouping genetic algorithm with local search to solve this problem. We have compared our approach with the state-of-the-art approaches reported in the literature. Computational results show the effectiveness of our approach.

关键词： steady-state grouping genetic algorithm Cellular-based wireless communication network Registration area planning Evolutionary algorithm

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