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A Novel Heuristic Optimization Algorithm for Solving the Delay-Constrained Least-Cost Problem

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Machine Learning for Networking (MLN 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12629))

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Abstract

The quality of the multicast routing service (QoS) is an NP multi-objective optimization problem. It is one of the main issues of transmission in communication networks that consist of concurrently sending the same information from a source to a subset of all possible destinations in a computer network. Thus, it becomes an important technology communication. To solve the problem, a current approach for efficiently supporting a multicast session in a network is establishing a multicast tree that covers the source and all terminal nodes. This problem can be reduced to a minimal Steiner tree problem (MST), which aims to look for a tree that covers a set of nodes with a minimum total cost that has been proven to be NP-complete. In this paper, we propose a novel algorithm based on the greedy randomized search procedure (GRASP) for the Delay-Constrained Least-Cost problem. Constrained with the construction and improvement phase, the proposed algorithm makes the difference in the construction phase through using a new method called EB heuristic. The procedure was first applied to improve the KMB heuristic in order to solve the Steiner tree problem. Obtained solutions were improved by using the tabu search method in the enhancement process. Computational experiments on medium-sized problems (50–100 nodes) from literature show that the proposed metaheuristic gives competitive results in terms of cost and delay compared to the proposed results in the literature.

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Authors and Affiliations

  1. Laboratory of Mathematics and Applied Mathematics (LMAM), University of Jijel, Jijel, Algeria

    Amina Boudjelida & Ali Lemouari

Authors
  1. Amina Boudjelida
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  2. Ali Lemouari
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Correspondence to Amina Boudjelida or Ali Lemouari .

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Editors and Affiliations

  1. Laboratoire LIGM UMR 8049 CNRS, ESIEE Paris, Noisy-le-Grand, France

    Éric Renault

  2. CNAM/CEDRIC, Paris, France

    Selma Boumerdassi

  3. Inria/EVA Project, Paris, France

    Paul Mühlethaler

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Boudjelida, A., Lemouari, A. (2021). A Novel Heuristic Optimization Algorithm for Solving the Delay-Constrained Least-Cost Problem. In: Renault, É., Boumerdassi, S., Mühlethaler, P. (eds) Machine Learning for Networking. MLN 2020. Lecture Notes in Computer Science(), vol 12629. Springer, Cham. https://doi.org/10.1007/978-3-030-70866-5_23

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  • DOI: https://doi.org/10.1007/978-3-030-70866-5_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-70865-8

  • Online ISBN: 978-3-030-70866-5

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