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whale optimization » swarm optimization (Expand Search), based optimization (Expand Search)
whale optimization » swarm optimization (Expand Search), based optimization (Expand Search)
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DRL-Based IRS-Assisted Secure Visible Light Communications
Published 2022“…Our objective is to optimize the Secrecy Capacity (SC) by finding the optimal beamforming (BF) weights equipped at the VLC fixtures and mirror orientations at the mirror array sheet. …”
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An Improved Genghis Khan Optimizer based on Enhanced Solution Quality Strategy for Global Optimization and Feature Selection Problems
Published 2024“…To assess the efficacy of the I-GKSO, it has been subjected to comparisons with multiple different algorithms. The trials conducted using FS datasets yield a quantitative consideration of the I-GKSO's capacity to attain the most optimal subset of features. …”
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A simulated annealing algorithm for the capacitated vehicle routing problem
Published 2017“…The Capacitated Vehicle Routing Problem (CVRP) is a combinatorial optimization problem where a fleet of delivery vehicles must service known customer demands from a common depot at a minimum transit cost without exceeding the capacity constraint of each vehicle. …”
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A simulated annealing algorithm for the capacitated vehicle routing problem
Published 2011“…The Capacitated Vehicle Routing Problem (CVRP) is a combinatorial optimization problem where a eet of delivery vehicles must service known customer demands from a common depot at a minimum transit cost without exceeding the capacity constraint of each vehicle. …”
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A modified coronavirus herd immunity optimizer for capacitated vehicle routing problem
Published 2021“…Capacitated Vehicle routing problem is NP-hard scheduling problem in which the main concern is to findthe best routes with minimum cost for a number of vehicles serving a number of scattered customersunder some vehicle capacity constraint. Due to the complex nature of the capacitated vehicle routingproblem, metaheuristic optimization algorithms are widely used for tackling this type of challenge.Coronavirus Herd Immunity Optimizer (CHIO) is a recent metaheuristic population-based algorithm thatmimics the COVID-19 herd immunity treatment strategy. …”
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Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm
Published 2020“…Abstract The topology design of switched enterprise networks (SENs) is a hard constrained combinatorial optimization problem. The problem consists of deciding the number, types, and locations of the network active elements (hubs, switches, and routers), as well as the links and their capacities. …”
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Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm
Published 2020“…Abstract The topology design of switched enterprise networks (SENs) is a hard constrained combinatorial optimization problem. The problem consists of deciding the number, types, and locations of the network active elements (hubs, switches, and routers), as well as the links and their capacities. …”
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Multi-Agent Variational Approach for Robotics: A Bio-Inspired Perspective
Published 2023“…The effectiveness of the proposed MAE-PAO methodology is verified through extended simulations in various environmental conditions. The algorithm viability is further evaluated by comparing the results with those of the contemporary CME-Aquila Optimizer (CME-AO) and the Whale Optimizer. …”
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Optimal Routing and Scheduling in E-commerce Logistics using Crowdsourcing Strategies
Published 2017Get full text
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Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling
Published 2022“…A Stochastic Discrete Simulation-Based Multi-Objective Optimization (SDSMO) model is developed and linked to clustering algorithms using an iterative sequential approach. …”
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Assessment of Inventory and Transportation Collaboration in a Logistics Marketplace
Published 2020Get full text
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Enhancing e-learning through AI: advanced techniques for optimizing student performance
Published 2024“…AI algorithms, known for their cognitive ability and capacity to learn, adapt, and make decisions, are employed to analyze and forecast student performance, thereby improving educational quality and outcomes. …”
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Optimal Dispatch of Mobile Energy Storage Unit to Support EV Charging Stations
Published 2021Get full text
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Mobile Energy Storage Systems for Benefit Maximization in Resilient Smart Grids
Published 2025Get full text
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On-site workshop investment problem: A novel mathematical approach and solution procedure
Published 2023“…Computational experiments show that the proposed method has solved most of the instances of the addressed problem to optimality and outperformed the existing metaheuristics, e.g., Simulated Annealing (SA) and Particle Swarm Optimization (PSO). …”
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Matheuristic Fixed Set Search Applied to the Two-Stage Capacitated Facility Location Problem
Published 2025“…The need for effective solution methods arises from the problem’s large-scale complexity and the strong influence of spatial and capacity constraints on solution quality. We propose a twofold contribution: first, an adaptive greedy algorithm that generates high-quality initial solutions, achieving markedly better results than traditional constructive heuristics at comparable computational costs; and second, the adaptation of the Matheuristic Fixed Set Search (MFSS) to the TSCFLP. …”
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A combined resource allocation framework for PEVs charging stations, renewable energy resources and distributed energy storage systems
Published 2017“…The formulation is decomposed into two interdependent sub-problems and solved using a combination of metaheuristic and deterministic optimization techniques. A sample case study is presented to illustrate the performance of the algorithm.…”
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DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave Communications
Published 2024“…The aim is to enhance the secrecy capacity (SC) of the system by optimizing the beamforming weights at the VLC fixtures, the beamforming weights at the mmWave AP, the mirror array configurations, and the phase shift vector while meeting specific power constraints. …”
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Enhancing Healthcare Systems With Deep Reinforcement Learning: Insights Into D2D Communications and Remote Monitoring
Published 2024“…By formulating the video resource allocation challenge as a multi-objective optimization problem, the framework aims to minimize network delays while respecting node capacity limitations. …”
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