GRASP for Assignment Problem in Telecommunications

Carlos A. S. Oliveira ()
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Carlos A. S. Oliveira: AT&T Labs Inc.

Chapter Chapter 10 in Handbook of Artificial Intelligence and Data Sciences for Routing Problems, 2025, pp 177-201 from Springer

Abstract: Abstract The Frequency Assignment Problem is a critical issue in telecommunications, where the goal is to assign frequencies to transmitters while minimizing interference across the network. Given the NP-hard nature of FAP, finding optimal solutions within polynomial time is infeasible, prompting the need for effective heuristic methods. Our focus is on adapting GRASP to address the specific challenges, including the management of local, co-channel, and adjacent channel interference. We describe the problem’s formulation, the components of a typical FAP instance, and the objective function used to evaluate potential solutions. The chapter elaborates on the GRASP methodology, highlighting the use of restricted candidate lists (RCL) and iterative construction of solutions to enhance the quality and feasibility of frequency assignments. The effectiveness of the proposed GRASP-based approach is demonstrated through its ability to generate high-quality solutions that balance interference minimization with constraint satisfaction. By analyzing the results, we identify patterns and optimizations that contribute to improved performance in real-world applications. This work contributes to the broader field of combinatorial optimization in telecommunications engineering, offering insights into the application of metaheuristics for complex, large-scale problems.

Keywords: Frequency assignment; Optimization; Greedy algorithms; Local search (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/978-3-031-78262-6_10

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