Search Trajectory Networks Applied to the Cyclic Bandwidth Sum Problem



Narvaez-Teran V, Ochoa G & Rodriguez-Tello E (2021) Search Trajectory Networks Applied to the Cyclic Bandwidth Sum Problem. IEEE Access, 9, pp. 151266-151277.

Search trajectory networks (STNs) were proposed as a tool to analyze the behavior of metaheuristics in relation to their exploration ability and the search space regions they traverse. The technique derives from the study of fitness landscapes using local optima networks (LONs). STNs are related to LONs in that both are built as graphs, modelling the transitions among solutions or group of solutions in the search space. The key difference is that STN nodes can represent solutions or groups of solutions that are not necessarily locally optimal. This work presents an STN-based study for a particular combinatorial optimization problem, the cyclic bandwidth sum minimization. STNs were employed to analyze the two leading algorithms for this problem: a memetic algorithm and a hyperheuristic memetic algorithm. We also propose a novel grouping method for STNs that can be generally applied to both continuous and combinatorial spaces.

Search trajectory networks; cyclic bandwidth sum problem; hyperheuristics; memetic algorithms; hybridization

IEEE Access: Volume 9

FundersConsejo Nacional de Ciencia y Tecnologia-Mexico
Publication date31/12/2021
Publication date online13/11/2021
Date accepted by journal30/10/2021
PublisherInstitute of Electrical and Electronics Engineers (IEEE)

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Professor Gabriela Ochoa

Professor Gabriela Ochoa

Professor, Computing Science

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