Monographies

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Author: search.filters.author.Meraihi, YassineHas files: No

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    Binary whale optimization algorithm for topology planning in wireless mesh networks
    (Elsevier, 2023) Taleb, Sylia Mekhmoukh; Meraihi, Yassine; Mirjalili, Seyedali; Yahia, Selma; Ramdane-Cherif, Amar
    The objective of this research is to tackle the topology planning issue in Wireless Mesh Networks (WMNs) through the implementation of a Binary Whale Optimization Algorithm (BWOA). S-shaped and V-shaped families of transfer functions are employed to obtain a binary versions of WOA. BWOA is designed to reduce the number of mesh routers needed to meet the full coverage and full connectivity requirements. The performance of BWOA is evaluated using three metrics, namely the minimum, maximum, and average number of mesh routers, while taking into account variations in the number of mesh clients. According to the findings of the simulations carried out in Matlab®, BWOA algorithms utilizing V-shaped transfer functions outperform S-shaped transfer functions-based BWOA algorithms in terms of required number of mesh routers.
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    An enhanced whale optimization algorithm with opposition-based learning for LEDs placement in indoor VLC systems
    (Elsevier, 2023) Benayad, Abdelbaki; Boustil, Amel; Meraihi, Yassine; Mirjalili, Seyedali; Yahia, Selma; Taleb, Sylia Mekhmoukh
    Visible Light Communication (VLC) is a new technology that has attracted lately much interest from researchers and academics. It allows communication between users using photo-detectors (PDs) as receivers and light emitting diodes (LEDs) as transmitters. The deployment of LEDs in indoor VLC Systems is an important issue that affects the coverage of the network. In this article, we propose an improved version of Whale Optimization Algorithm, named EWOA, to resolve the LEDs placement problem in indoor visible light communication (VLC) systems. The EWOA is based on the integration of chaotic map concept and Opposition based learning method (OBL) into the standard WOA to improve its optimization performance. By taking into account the user throughput and coverage metrics while employing several produced instances and evaluating results against some meta-heuristics, the usefulness of EWOA was confirmed. The meta-heuristics that we used in the comparison are WOA, (MRFO) Manta Ray Foraging Optimizer, (CHIO) Herd immunity coronavirus optimizer, (MPA) Marine Predator Algorithm, (BA) Bat Algorithm, and (PSO) Particle Swarm Optimizer. The results showed that EWOA is more effective in finding optimal LEDs positions.
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    A hybrid whale optimization algorithm with tabu search algorithm for resource allocation in indoor VLC systems
    (Elsevier, 2023) Yahia, Selma; Meraihi, Yassine; Mirjalili, Seyedali; Taleb, Sylia Mekhmoukh; Refas, Souad; Ramdane-Cherif, Amar; Eldeeb, Hossien B.
    This paper proposes a novel hybrid approach (WOATS) based on the hybridization of Whale Optimization Algorithm (WOA) with Tabu search Algorithm (TS) for solving the resource allocation problem for indoor multi-user downlink VLC systems. The efficiency of the proposed WOATS is validated in several scenarios under different settings, considering the throughput and fairness parameters. The results demonstrated that WOATS provides competitive performance in optimizing resource allocation in indoor VLC systems compared to WOA, TS, Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Arithmetic Optimization Algorithm (AOA), Moth Flame Optimization (MFO), Grey Wolf Optimizer (GWO), and Sine Cosine Algorithm (SCA).