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A Hybrid Immunological Search for the Weighted Feedback Vertex Set Problem

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Learning and Intelligent Optimization (LION 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11968))

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Abstract

In this paper we present a hybrid immunological inspired algorithm (Hybrid-IA) for solving the Minimum Weighted Feedback Vertex Set (M W F V S) problem. MWFVS is one of the most interesting and challenging combinatorial optimization problem, which finds application in many fields and in many real life tasks. The proposed algorithm is inspired by the clonal selection principle, and therefore it takes advantage of the main strength characteristics of the operators of (i) cloning; (ii) hypermutation; and (iii) aging. Along with these operators, the algorithm uses a local search procedure, based on a deterministic approach, whose purpose is to refine the solutions found so far. In order to evaluate the efficiency and robustness of Hybrid-IA several experiments were performed on different instances, and for each instance it was compared to three different algorithms: (1) a memetic algorithm based on a genetic algorithm (MA); (2) a tabu search metaheuristic (XTS); and (3) an iterative tabu search (ITS). The obtained results prove the efficiency and reliability of hybrid-IA on all instances in term of the best solutions found and also similar performances with all compared algorithms, which represent nowadays the state-of-the-art on for MWFVS problem.

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of Catania, V.le A. Doria 6, 95125, Catania, Italy

    Vincenco Cutello, Maria Oliva, Mario Pavone & Rocco A. Scollo

Authors
  1. Vincenco Cutello
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  2. Maria Oliva
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  3. Mario Pavone
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  4. Rocco A. Scollo
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Corresponding authors

Correspondence to Vincenco Cutello or Mario Pavone .

Editor information

Editors and Affiliations

  1. Technical University of Crete, Chania, Greece

    Nikolaos F. Matsatsinis

  2. Technical University of Crete, Chania, Greece

    Yannis Marinakis

  3. Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, USA

    Panos Pardalos

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Cutello, V., Oliva, M., Pavone, M., Scollo, R.A. (2020). A Hybrid Immunological Search for the Weighted Feedback Vertex Set Problem. In: Matsatsinis, N., Marinakis, Y., Pardalos, P. (eds) Learning and Intelligent Optimization. LION 2019. Lecture Notes in Computer Science(), vol 11968. Springer, Cham. https://doi.org/10.1007/978-3-030-38629-0_1

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